Array Ventures Insights

HappyRobot, Sapiom, and Agency

Shruti Gandhi — Thu, 06 Aug 2026 14:12:06 GMT

Big week for Array Ventures.

Excited to celebrate major milestones from three portfolio companies: HappyRobot, Sapiom, and Agency. Array invested in first rounds of all 3 of these companies.

Couldn’t be happier for these founders and teams. It’s a privilege to back builders this early and watch these moments unfold. Building great companies takes years, and it’s always special to see the hard work pay off. Onward 🚀

Happyrobot raises $150M Series C at $1.2B valuation

Check out their post here.

When Pablo, Javi, and Luis first pitched to me from Germany, they hadn’t raised anything. What stood out wasn’t just the idea it was their energy, curiosity, willingness to experiment, and relentless optimism. None of us could stop cracking jokes and smiling!

Three years later, they’ve charted an incredible course with that same mindset. Sometimes in venture, it’s the people more than anything else that make all the difference.

Also grateful for our LP to become one of their early customers when Happyrobot moved into logistics! It does take a very open minded community!

Congrats to the team on doing all this along the way with all other life updates in parallel! So proud of them! It’s certainly not easy as they make it seem!

See our post here.

Sapiom raised $50 million in total funding since inception

Check out their post here.

A year ago when we invested in Sapiom most investors thought autonomous agents were too early. Sapiom now has processed 270 million transactions across more than 100,000 agents daily.

When I met Ilan Zerbib he had left Shopify three weeks earlier. His thesis was simple: autonomous agents would need their own budgets, permissions and ways to buy resources.

We had already run into this problem while testing agents in Array’s own stack at the Array Ventures AI lab. Nothing else on the market solved it for the enterprise, so we led Sapiom’s pre-seed round and decided to invest on the spot!

Since then Accel led their seed round & Dragonfly has joined the journey now leading their Series A. What looks obvious now was not obvious then. Congrats to Ilan and the Sapiom team. I am very excited for their journey and how easy it has made for us at Array to use our agents!

See our post here.

Agency has been acquired by Klaviyo

Check out their post here

Elias Torres and I go back more than two decades to our days at IBM, where we worked together on the cutting-edge WebAhead team. Since then, I’ve had the privilege of watching Elias build multiple exceptional companies, including Drift, which was acquired by Vista Equity Partners for $1.2 billion.

When Elias began exploring what to build next, we spent countless hours experimenting with the new generation of AI tools. Those explorations ultimately became Agency, and Array Ventures was proud to be one of the company’s earliest commitments.

It’s incredibly rewarding to see this come full circle for Elias and the entire Agency team. I also love how this story mirrors our history; Elias now gets to build alongside his longtime friend, Andrew Bialecki, CEO of Klaviyo. At the end of the day, this business is built on relationships. The best partnerships often span decades blurring lines between business and friendships.

Congratulations to Elias and the entire Agency team. We’re excited to see what comes next.

Every industry is being rebuilt with AI, robotics, and next gen infrastructure. Array Ventures invests $250K–$3M at inception in the foundational companies transforming the world’s largest industries. If you’re building the future of an industry we’d love to hear from you deals@array.vc

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Loop to Graph Engineering for Measuring AI Spend

Shruti Gandhi — Wed, 22 Jul 2026 16:11:37 GMT

AI Spend as we all know is getting hard to manage and Loop and Graph Engineering are great way to measure AI spend and productivity

1. Stop prompting agents. Start designing loops.

2. Move from Loops to Graph Engineering

Most companies I talk to are still asking the practical question: what do loops and graphs actually mean for a company?

The prompt engineering way was simple. You asked the model for something. It gave you an answer. You read it, decided what was wrong, added more context, and asked again. The model helped with the work, but you still managed every turn.

You were doing the hidden parts of the workflow: deciding what to try next, checking whether the answer was useful, remembering what already failed, and knowing when to stop. In practice, you were the loop.

The easy take is that prompt engineering is dead. I do not think that is quite right. Prompting is not going away. It is moving up a level. A prompt is a single instruction. A loop is a job with a process around it.

Instead of telling the agent what to do every turn, you define the goal, tools, checks, and stop conditions that let it keep working without you. They turn model output into work that can be accepted, rejected, retried, priced, and improved.

Prompting versus looping

That made sense when AI was mostly a chat box.

It starts to break once AI becomes an agent.

Agents can read files, call tools, search systems, write code, open tickets, update CRMs, and trigger workflows across software. Once the system can act, the hard part is no longer writing the perfect prompt. The hard part is designing the process around the agent.

That process is the loop.

A real loop has 5 steps.

Discover: work out what needs to happen.
Plan: choose the next action.
Execute: do the work with tools.
Verify: compare the result to the goal.
Iterate: feed the result back in and try again if it failed.

The agent needs state, so it does not repeat the same mistake every pass. It needs a stop condition, so it does not run all night. It needs a real check on the work, or it will just agree with itself until your token budget is gone.

This is the difference between a prompt and a loop. A prompt gives the model an instruction. A loop gives the model a job, a way to know whether the job is done, and a rule for when to give up.

What is a loop?

Here is the simplest coding version.

Goal: fix the auth tests.

Each pass: run the tests, read the failure, make the smallest useful change, run the tests again.

Success: auth tests pass, type checks pass, lint is clean.

Stop: success, or eight attempts with a summary of what still fails.

That is a loop. Not because it uses AI. Because the system can keep moving without a human prompting every step.

Coding is where this is showing up first because software already has feedback built in.

Tests fail. Builds break. Type errors show up. The agent can try a fix, run the checks, read the failure, change the code, and try again.

That is why coding agents feel ahead of the rest of the agent market. Developers adopted them early, but code also gives agents a clean environment to improve inside.

The same pattern is coming to other workflows, but the moves changes by industry.

In support, the accepted output is a resolved ticket. In finance, it is a reconciled invoice. In sales, it is a qualified account. In compliance, it is an exception cleared or routed to the right reviewer.

The business value becomes clearer when each loop produces a result that can be accepted or rejected. This gives companies a way to measure AI work through completed outcomes rather than tokens used or agent runs.

We think of each accepted result as an Accepted Work Unit.

Once the output can be accepted or rejected, a company can measure its cost per accepted work unit.

This connects AI spend to work the business already understands.

AI Spend Measured In Cost per accepted work unit

Many agent demos feel better than they actually are.

A demo can show a lot of motion. Tabs open, tools fire, agents talk to each other, and a task appears to move forward.

Buyers do not pay for motion. They pay for completed work they can trust.

Zendesk is already moving in this direction with outcome-based AI pricing for support. Customers pay when a problem is resolved, not when an agent runs.

That is the right mental model. AI agents should not be measured like software seats. They should be measured more like labor.

What did they complete? How often was it accepted? How often did a human step in? What did each accepted unit cost?

That is a higher bar than a demo. It is also a much bigger company-building opportunity.

Measuring this reliably creates room for a new infrastructure layer. The next AI stack will look less like chat and more like operations infrastructure for loops and graphs. The generic version of this stack is already becoming standard: sandboxes, evals, observability, permissions, connectors. The loop-specific version is more interesting.

A production loop needs a job spec, so the agent knows the goal, scope, and definition of done. It needs a state ledger, so run 12 knows what runs 1 through 11 already tried. It needs a tool envelope, so the agent can act but only inside approved boundaries.

It also needs a gate, so soft completion does not count as real completion. It needs a budget policy, so the loop stops before it burns through tokens or creates review debt. It needs an escalation queue, so uncertain work lands with a person instead of getting silently accepted.

That is the LoopOps stack which is not just infrastructure for agents. Infrastructure for repeated AI work.

Risks Solved with LoopOps Stack

1. Ralph Wiggum failure

The agent declares the job done too early. The loop accepts that soft completion signal, exits, and leaves a half-finished result behind. Without a hard gate, loops fail quietly. That’s known as the mode loop.

This usually comes from three things: no real verifier, soft completion conditions, and no hard stop.

The fix is not another agent with an opinion. It is an objective gate. A test that passes or fails. A build that compiles or does not. A linter that returns zero or non-zero. A policy check that blocks the action.

2. Goal drift

Agentic laziness where the loop decides “done enough” is done. Goal drift over long sessions. Self-preferential bias when the same agent grades its own work.

3. Flawed Loop

A loop can call the wrong tool with the right-sounding reason, or store a bad assumption and repeat it every morning. The worst case is not always one catastrophic action. Sometimes it is a slow pileup of review debt, token spend, and quiet errors.

This is why I do not think loop engineering is just a prompt trick. It is closer to operations design.

Verrtical AI Loop create Differentiation

A generic loop can run the pattern but a vertical loop knows the messy details that make the pattern useful: the data, the edge cases, the customer workflow, the regulatory constraint, the escalation path.

That is where defensibility starts. Not in having another agent but in owning the feedback loop for a specific kind of work.

The best AI companies will not replace an entire job on day one. The more likely path is that companies automate repeatable loops inside a job first. Password resets before full customer support. Invoice matching before full finance ops. Test fixing before full engineering ownership. Account research before full sales replacement.

Each loop earns trust by doing a narrow slice of work at a known quality and cost. That is how AI labor enters the enterprise: workflow by workflow, not all at once in each vertical.

At Array, we are interested in founders building this layer. Agent infrastructure, vertical AI, workflow automation, AI ops, eval systems, and the boring-but-beautiful systems that make agents useful in production.

If you are building here DM or email me shruti@array.vc

Loop engineering is not the end of prompting. We also dive into Graph Engineering next. So follow us to see that next!

Array VC Insights: IPOs & AI Jobs

Shruti Gandhi — Fri, 22 May 2026 15:41:03 GMT

2026 IPO Watchlist

SpaceX ($1.75T), OpenAI & Anthropic ($1T), Stripe, Databricks, Revolut, Brex, Waymo, Anduril, and so many more!

AI Orchestrator is the Job

70k+ layoffs this year across 17 companies like Meta, Intuit, Block, Coinbase, Snowflake show middle managers were hit the hardest.

“The AI Orchestrator” is the Job of the Year for 2026. Maybe they can all pivot?

Cerebras Journey…Deeptech is hard and many AI / Robotics startups on a similar journey

Based on the S-1 filing of Cerebras they raised over $800m before they added any revenue. What it takes to do deeptech…

Imagine it takes 9 years to convince investors what you have is a good market, company, real contracts. The founder definitely lost a lot of hair over that decade!

Array Ventures invests $250k-$3m checks at formation. If you are starting a company in AI Infrastructure, making any industry such as healthcare, finance, manufacturing, supply chain, etc. better. Email us at deals@array.vc.

Thanks

Array Ventures Team

Our content is getting insightful everyday. You can get those updates in between these emails on X and LinkedIn.

Agents broke the security stack

Shruti Gandhi — Tue, 28 Apr 2026 16:08:03 GMT

We made three security investments at Array Ventures this year in these areas of data security, network security, and employee security testing. We are looking for more.

The security stack we built for the last 20 years assumed a human was somewhere in the loop. Agents are breaking the stack and humans can’t make sense of it. Worse of it insurance companies can’t make sense of it.

Investment 1: Agents broke data security

The first thing AI agents broke is data security. It’s already happening. Most security teams can’t see it.

April 2026. Vercel got breached without anyone touching Vercel. The attackers compromised Context.ai, a third-party AI assistant a Vercel employee had connected to their Google Workspace. They stole the OAuth tokens, took over the Google account, pivoted into Vercel’s internal systems, and walked out with 580 employee records. The database is on a hacker forum right now. No exploit. No phishing. Just an AI assistant, three companies removed from where the breach started.

2025. Researchers disclosed EchoLeak, a vulnerability in Microsoft 365 Copilot. An attacker sends an email with prompt injection hidden in the markdown. Copilot reads it automatically, follows the hidden instructions, and exfiltrates SharePoint and Teams data through approved Microsoft URLs. No human ever opens the email. No alert fires.

Both attacks share one property the old stack can’t handle: the actor isn’t a person. It’s a process. It has tokens. It has admin permissions. It moves data through syscalls.

There are now roughly 100 non-human identities inside the average enterprise for every human user. Most security teams can’t even inventory their own.

Endpoint security watches keyboards and screens. DLP writes rules per app. SaaS security tracks login flows. None of it catches an agent. Write a new rule and the agent has already found ten ways around it.

IBM’s 2025 report puts the average breach at $10.22M and the average detection time at 241 days. By the time you find out, your data has been moving for eight months.

Investment 2: Agents broke trust at the network layer

Your website doesn’t run on one thing. It runs on a stack of internet plumbing most people never see. DNS maps your domain to an IP. BGP routes traffic to that IP. TLS proves the server is really you. JavaScript is the actual code running in your customers’ browsers.

Each layer was secured separately. Each layer mostly works. But attackers figured out years ago that you don’t need to break a layer if you can compromise the trust between layers.

2024. Polyfill.io. A Chinese company bought the domain. 100,000+ websites loaded JavaScript from it, including Intuit, Mercedes-Benz, and the World Economic Forum. Months later, the new owners started serving malware. The TLS was valid. The DNS resolved correctly. The script came from the same trusted endpoint everyone had used for years. No single-layer tool was watching the gap between who owned the domain and what the script did.

For years, cross-layer attacks were rare enough that most companies got away with not thinking about them. That’s changing fast. Enterprise traffic is now mostly machine-to-machine. AI agents call APIs and load third-party code without a human in the loop. The blast radius of a single chain attack is bigger than it’s ever been.

Attackers are also using AI to probe for these gaps. A category of attack that used to require expert craftsmanship now runs at scale.

Crypto exchanges. Banks. Healthcare portals. Tax filing services. Anyone whose business depends on customers reaching the right server through the right code. This is where impersonation attacks become regulatory incidents and lost customer trust at scale.

Investment 3: The breach isn’t what kills you. The response does.

The most expensive part of a breach isn’t the technical exploit. It’s the chaos inside the company afterward.

70% of security leaders say internal chaos during a breach causes more damage than the attack itself (Cytactic CIRM Report 2025). 57% say their most recent incident was something they had never seen before. The runbooks and the dry runs do not survive contact with the actual fight.

MGM, 2023. A 10-minute social engineering call to the IT help desk. The response cost over $100M. Slot machines, hotel keys, ATMs, and websites went down across 30+ properties. Staff reverted to pen and paper. Guests waited hours in lines. Nobody could tell them whether the outage would last a day or three weeks.

Here’s the structural problem: 150,000 security teams worldwide run the same compliance-mandated crisis exercise every year. A static narrative, written months earlier. No surprises. No adaptation. Teams check the box and move on. When a real attack arrives that nobody has seen before, nobody has rehearsed for it.

Crisis preparation is the part of security that has never scaled. The technical layer keeps getting better every year. Detection. Prevention. Endpoint. Network. The human and organizational layer of incident response has barely moved. Putting a team through realistic crisis pressure used to require flying in expensive specialists, which only the largest enterprises could afford.

AI is the first technology that makes adaptive crisis preparation tractable for everyone else.

What we already backed

One bet in each layer this year:

Data movement governance for agents. A team rebuilding DLP at the kernel level, treating agents and humans as the same kind of process moving data through syscalls.

Web infrastructure security. Catching impersonation attacks that exploit gaps between the layers of the web stack. The kind no single tool sees.

Adaptive crisis training. Replacing the static compliance tabletop with AI adversaries that probe, adapt, and force teams to rehearse for the attacker they’ll actually face.

Where we’re still looking

We’re actively writing checks in:

Agent identity and authority management. Non-human identities outnumber humans 100 to 1. Most companies can’t inventory theirs.

Autonomous SOC and incident response. Defenders need to match offense’s clock speed.

AI red-teaming and pre-deployment testing. Models ship faster than testing tools can keep up. We want the team that fixes this.

Vibe coding security. Agents are shipping production code with security holes baked in. Nobody has solved it.

How are you thinking about security in your stack? What’s the gap that worries you most?

If you’re building a company in any of these areas, email us deals@array.vc.

11 companies cracked 1M ARR in 6 months with DAD

Shruti Gandhi — Tue, 03 Mar 2026 19:57:53 GMT

These companies went from 0-1M ARR in under 6 months with distribution first and tiny teams. Distribution as Differentiation (DAD)… SEO, community, or PLG > paid ads in all these cases.

1.⁠ ⁠Base44. sold for $80M in 6 months. Maor Shlomo. bootstrapped. created founder led content on LinkedIn that resonated with his “builder” audience.

2.⁠ ⁠RunPod. $120M ARR in 4 years. two devs turned crypto mining rigs into AI servers. first users came from a Reddit post offering free GPU time.

3.⁠ ⁠CalAI. $50M ARR in 18 months. teens. cold DM’d hundreds of TikTok creators, personally coached their hooks to 2-3x their views.

4.⁠ ⁠Arcads. $13M ARR in under 2 years. duo. ran their own paid ads for years, then built the AI tool to automate what he was doing by hand.

5.⁠ ⁠BoredHumans. $8.8M ARR in ~2 years. Eric Borgos, self-taught. built 100+ simple AI tools and built Google traffic with boring SEO-optimized utility pages.

6.⁠ ⁠HeadshotPro. $3.6M ARR in 2 years. Danny Postma built it in 30 hours when Stable Diffusion dropped. 200+ programmatic SEO pages for distribution.

7.⁠ ⁠Photo AI. $1.6M ARR in 2.5 years. Pieter Levels. zero employees. shipped X/LI 70+ projects before finding the ones that stuck.

8.⁠ ⁠ShipFast. $80K/month in 2 years. Marc Lou built his X and YouTube audience for 1.5 years first. the personal brand is the startup.

9.⁠ ⁠Interview Coder. $1M ARR, 36 days. Roy Lee. filmed himself using AI to cheat live tech interviews. 50M+ views on X/LI. the controversy was the marketing.

10.⁠ ⁠Lovable. $200M ARR in 12 months primarily on Github. built a community before launch on hackernews and product hunt. created a mini prodcut hunt for their community to launch lovable apps. 316 projects were submitted in the launch week.

11. Musicfy $1.5M ARR. Arib Khan built in 7 days at age 19. tool went viral with 100k users from AI-generated covers of popular artists like Drake and Kanye West. early traction from niche communities on Discord.

How Our 24/7 AI Coworker Replaced Half Our Internal Tools

Shruti Gandhi — Tue, 17 Feb 2026 15:01:33 GMT

An AI coworker that runs around the clock, manages its own files, remembers everything we’ve discussed over the past few months, and messages us on WhatsApp when something needs attention. That’s what we’ve been running at Array and it’s changed how we operate every day.

We launched Array AI Labs last year and went through a lot of iterations to get here. Early versions were just a static dashboard and AI workflows on triggers. Really useful but unable to think for itself or pick up where it left off. Here’s what actually made the difference.

It Remembers Everything

The turning point was when our agent got a memory layer that actually persists. Structured memory that updates as it learns about our team, our projects, and how we work. It knows who it’s talking to, what we care about, and what happened in conversations from weeks ago without anyone having to remind it.

We also built background processes that take everything the agent has seen and turn it into a searchable knowledge base so it gets smarter the longer it runs.

It Works While We Sleep

We set up a heartbeat, a pattern OpenClaw made popular. The agent wakes up on a schedule, checks what’s happened, reviews open tasks, and flags anything that needs our attention. If something breaks overnight our system catches it. If a task stalled it reminds us to review.

We also connected it to WhatsApp and Slack so we can reach it from anywhere.

It Builds Its Own Tools

Once your agent is running in a sandbox with its own filesystem, you realize it can do a lot more than answer questions. It can build things.

We started with a standard operations dashboard that worked fine until every week someone needed a new view or a different chart. Requests would pile up for days. So I handed the agent a spreadsheet and said build me a dashboard. It spun up a working app with live data in minutes.

Now instead of requests piling up, anyone on the team just messages the agent. It updates the code, rebuilds, and it’s live. What started as a dashboard has turned into our internal operating system. The agent maintains it and it moves as fast as we do.

What Surprised Us

The model matters way less than we expected. What actually makes the difference is whether the agent can hold context over time and keep learning from every conversation.

We didn’t expect how much sandboxing would matter. Once your agent is running 24/7 with real filesystem access, having it isolated in its own environment so it can work freely without risk turned out to be essential.

Loading a bunch of integrations at once actually makes agents worse. They spend half their context reading tool definitions instead of doing the work. Giving the agent skills it can pick up on demand and put down when it’s done made everything faster and more reliable.

And the things that sound small but ended up being real unlocks: putting the agent on WhatsApp so we don’t have to open a laptop to talk to it, letting the agent schedule its own tasks, and giving each agent its own email and phone number instead of sharing ours. That last one turned out to be important for security reasons we didn’t think about early enough.

What’s Next

We’re seeing teams start to connect multiple coworkers together. We’ve been experimenting with A2A protocols and exposing each agent as an MCP server so other agents and tools can call them directly. Multi-agent memory is the other big challenge since getting memory right for even a single agent is still evolving rapidly. For now one main agent with sub-agents it can call in parallel for specific tasks is what’s working best for us.

The space is moving incredibly fast and I feel lucky that our team gets to build with these tools every day. If you’re working on any of the infrastructure that makes this possible, I would love to talk.

Array Ventures invests $250K-$3M at formation in AI infrastructure. We use what we invest in. Email deals@array.vc.

[Array VC] Exciting Updates, Investments, Market Trends, & AI Opportunities

Shruti Gandhi — Wed, 11 Feb 2026 18:11:55 GMT

At Array Ventures, we have had quite an active last few months and there are no signs of slowing down! We are hiring to keep up with our growing agents! Please apply here if you are a growth hacker interested in Venture Ops!

Portfolio News & Exits

Wabi.ai announced their $20M preseed from a16z and have been going viral. Check out how 8 year olds are building with Wabi and go build your app!
Sapiom.ai raises $15M from Accel to help agents buy their own tools
Catch Flamingo on MSP Chat podcast to hear why customers love Flamingo’s OpenSource AI Stack.
Congrats to Chisel on their acquisition by Pendo to help product teams build with agentic AI
Congrats to Tellen on acquiring a large Grant Thornton’s qm.x audit quality solution!
Hotdata is building a foundational piece of the agent data stack so agents can query data in milliseconds without moving data. Contribute to their project!
Retina Robotics showed off their barcode-free inventory tracking at Manifest!
Runable’s successful launch with over 1M views lets people build anything like your next deck, website, or podcast!
Expanso shared a zero-trust data access layer for AI agents and share their OpenClaw integration
Leapfin announces $12M raise from Crosslink to empower businesses with financial data.
CandorIQ rolled out a benchmarking product that helps companies understand how competitively they’re paying their employees. Also check out their agent management HR tool!
RM Growth is making waves with it’s simplified social-commerce tools. One fleet of AI agents that take over everything creators and sellers do manually today from managing group chats to coordinating orders to let sellers sell on any platform at scale.
Decision Computing has been publishing the playbook for building mission-critical AI agents safe in their latest posts.
Enterprises run table top exercises to stress test their cybersecurity measures and Reflex Security enables enterprises to simulate such attacks.
HappyRobot shared their partnership with DHL, C. H. Robinson, Mode Global and talk about how to make supply chain safer at Manifest!
Blaze recently opened access to autonomous multi-agent AI marketer that strategizes, creates, posts, and learns ongoing marketing content on behalf of users.
Runway launched FlightPaths, which gives teams unified visibility into all mobile app releases and lets them perform bulk actions and automations across apps.
Catch the Sotto AI founder talking about how the ticketing industry can market using AI.

Array AI Labs

We’ve been actively experimenting with the latest AI products, integrating them into our stack, and sharing our learnings online. Being early adopters is helping us stay close to where the market is moving.

We’ve also been able to spot and highlight some deeply buried features in new AI tools before they became widely known.

The Array Dashboard is now the Array Operating System: The Array dashboard got a major upgrade. We moved from a traditional dashboard setup to a fully agentic system that can take on multiple tasks beyond just operations. We now have specialized agents for marketing, reporting, and several other functions. These agents can function alone or in swarms and coordinate + communicate to get tasks done.

We’re not just investing in the AI stack. We’re running it. Six portfolio companies are already embedded in how we operate day to day, from Hotdata’s federated data layer to Meibel’s runtime orchestration, Sapiom for payments, Wokelo for research, Agency for our meetings intelligence, and Runable for AI-powered content and repeated tasks. Our investment thesis comes from what survives our own workflows.

Jobs

Find jobs at Array VC companies directly on our website. Our companies are hiring across Engineering, Marketing, Sales, and many more roles.

Multi-agent systems crossed the line from research to production this year. Specialized agents that own a domain, coordinate with each other, and run around the clock. Your next department hire will not be a person.

Shared Persistent Memory Infrastructure. Always-on agents generate thousands of decisions a day.

The UI layer is dissolving. Protocols like MCP-UI, AI-native app builders like LastApp, and agents that generate their own interfaces are killing the static dashboard. Your next internal tool might build itself.

Open models are now months behind the frontier, not years. Enterprises that need to own their stack are running both.

Ads are entering AI. As agents handle purchases and decisions, who gets placed inside an agent’s decision flow is the next billion-dollar question.

AI is leaving the screen. World models and robotic simulation are making it possible to train machines in synthetic environments before they touch the real world.

The median burn multiple has fallen below 1.5× for the first time since 2020. Companies are being efficient, revenues are kicking in early. Enterprises and SMBs are willing to pay, pilots are converting.

What Are We Looking To Invest Right Now?

We published a list of things here we are looking to invest and here are few additional things we will add. Email us deals@array.vc if you are building in any of these areas.

Long-Running Agents That Handle Chaos. If agents are the new hires, they need to handle the same mess real employees do. Multi-day tasks, broken integrations, changing requirements. We’re investing in the agents and infrastructure built for that reality.

Runtime Policy Engines. And just like employees, they need rules. Real-time guardrails that control what agents can do and self-correct when they go off track.

Shared persistent Memory Infrastructure for Agent swarms handling multiple tasks together as a team.

AI That Learns From How Humans Actually Work. Zero shot AI trained on Egocentric first-person footage of experts performing various tasks.

Multirobot Orchestration. An abstraction to operate, coordinate and perform tasks across a variety of robotic fleets, legacy robots and the latest AMRs.

Worldmodels. Physics-aware simulation engines that let robots, autonomous vehicles, and industrial systems train on thousands of synthetic scenarios before touching the real world. The infrastructure layer for building and deploying domain-specific world models.

Edge AI. The compression, runtime, and orchestration stack that makes every device intelligent without ever calling the cloud.

Consumer Interfaces. The next interface isn’t chat or voice. AI-native hardware and software that rewires how humans interact with information, make decisions, and navigate the physical world.

Array Ventures invests $250k-$3m checks at formation. If you are starting a company in AI Infrastructure, making any industry such as healthcare, finance, manufacturing, supply chain, etc. better. Email us at deals@array.vc.

Thanks

Array Ventures Team

Our content is getting interesting everyday with our AI experiments. You can get those updates in between these quarterly updates on X and LinkedIn.

Churn/Retention in the Era of AI

Shruti Gandhi — Fri, 06 Feb 2026 14:58:11 GMT

We recently ran a Customer Success Workshop for Array Ventures Portfolio Founders and gathered some really shocking insights.

AI companies are not just fighting churn. They are facing a retention apocalypse. Low-price AI tools (< $50/mo) experience very high churn with gross revenue retention GRR around ~23% and NRR ~32%, meaning ~70–80% of revenue churns within a year.

The a16z insight that clicked for me:

Don’t measure retention from Month 0. Measure from Month 3. AI tourists will churn in weeks 1-12. Your real retention curve starts when the hobbyists leave and you’re left with people who’ve integrated you into actual work.

Why AI Churn Can Be Higher

Easy to buy, easy to cancel: Simple sign-up makes initial adoption fast but also easy to drop.
Tourism Churn: Many downloads or trials reflect curiosity more than long-term commitment.
No workflow Integration: Products that don’t embed into core workflows tend to churn quickly.

Companies That Are Winning Do The Following

Move upmarket ($250+/month): 70% GRR / 85% NRR—basically matching SaaS
Build for habitual workflows (Lovable’s 100k apps/day speaks to this)
Add services/FDEs on top of AI (the Palantir playbook)

Some Tips For Founders

63% of customers decide whether they’ll renew within the first 30 days. Not at renewal time but during onboarding!!

Reverse-engineer onboarding around 3 product milestones your customers need to hit in the first 45 days. Ruthless focus on becoming irreplaceable in 2-3 core workflows before Month 3.
Comp your onboarding team on time-to-value.
Create a CSQL spiff. Your CSMs find the expansion opportunity, your AEs close it. CSM gets a flat $100-250 spot bonus per closed deal.
Don’t make CSMs guess who to upsell. Build dashboards showing each CSM the exact dollar delta of expansion opportunities in their book.

This is what Array looks like beyond the wire. Workshops, operator playbooks, real data from real portfolios. We invest $500K–$3M into technical founders building where AI creates leverage. If that’s you → deals@array.vc

We share what we’re learning from our AI Labs experiments on X and LinkedIn every day so follow us there.

Web World Models – Simple Explainer

Shruti Gandhi — Fri, 23 Jan 2026 18:33:53 GMT

The ability to train agents in realistic environments before being shipped to production, will unlock a new category in agent training infrastructure.

Problem: You can’t store an infinite world in a database. But agents need persistent environments. Places they can leave, come back to, and find exactly as they left them.

Right now there are two ways to build agent “simulators”:

Traditional software – Reliable but rigid. The agent can only do what developers explicitly coded. Like a flight sim where you can only fly to 5 airports.

Pure AI generation – The AI hallucinates the entire world, but nothing stays consistent. You fly back to an airport and suddenly it has 8 runways instead of 3.

Solution: Princeton’s new paper found a fix. Use regular code to enforce the rules (physics, inventory limits, what’s allowed) and let AI handle the texture (descriptions, dialogue, atmosphere). Every location has a unique address. That address always generates the same place – same buildings, same layout, same details. They are replacing storage with just math. They call it Web World Models (WWM).

Think video games where the engine handles character physics and health bars, the graphics layer handles the environment generation on the fly. So in GTA you can’t drive through buildings or spend money you don’t have but the streets could still feel alive with pedestrians and chatter.

Robots need the same thing – persistent, consistent environments to practice in before touching the real world. Warehouses, kitchens, factory floors where robots need to fail safely before touching the real world. The ability to train agents and robots in realistic environments before being shipped to production will unlock a new category in agent training infrastructure. WWMs offer a path to build those at scale.

How are you training and evaluating your agents today? What does your RL environment setup look like? If you’re building company to solve this problem email us deals@array.vc.

Our content is getting interesting everyday with our AI experiments. You can get those updates in between these quarterly updates on X and LinkedIn.

If AI Doesn’t Know You Exist, Users Won’t Either.

Shruti Gandhi — Tue, 20 Jan 2026 19:32:59 GMT

Google rankings takes months.

Google Page 1? Can take months
Organic CTR? Hovering around 2-3%
First qualified lead? Usually 6-8 weeks out

LLM ranking takes days.

Perplexity picking up content in under 48 hours
~20% of sessions coming from LLM-originated paths
Leads converting roughly 2-3x better than blog traffic

At Array we lead pre-seed/seed ($250K-$3M) into AI infrastructure, data, and deeptech. We saw what was working across 350+ pitches a week.

1. LLM.txt + context files as the new robots.txt

Create dedicated llm.txt or context files (product specs, pricing, ICP, use cases) and link them prominently in docs/onboarding. It gives models clean, hallucination-proof context.

Models pull from these when reasoning about categories.

2. Structured Q&A on every product page

Add 5-7 questions per page and answers under 40 words. Be specific and technical.

Example that worked:

Q: How does [product] handle cold start latency for serverless inference?

A: Pre-warmed containers with model sharding keep p99 latency under 200ms for models up to 7B parameters.

Specific = The LLM wants to cite,. Vague marketing fluff = it wants to ignore.

3. Use Reddit for clear product breakdowns

Post genuine breakdowns (e.g., “how we automated an agent pipeline,” tradeoffs, alternatives) without links or salesy vibes.

LLMs cite Reddit heavily for real-user problems and solutions.

One post explaining an agent architecture got quoted across 9 different Perplexity queries (”best alternatives to X,” “how to track LLM bots”). Two inbound leads came directly from it within 3 days.

4. Specialized sitemaps for AI crawlers

Beyond standard sitemaps, create a focused ai-sitemap.xml with high-signal pages only: API docs, feature comparisons, tech specs, pricing.

Example structure:

<ai-sitemap>
  <page>
    <loc>https://yoursite.com/features/inference</loc>
    <summary>Low-latency inference API for edge deployment</summary>
    <keywords>inference, edge AI, low-latency, API</keywords>
    <lastmod>2026-01-15</lastmod>
  </page>
</ai-sitemap>

Results seen: LLM crawl rates jumped 2.3x. Bots are now showing up daily in logs.

5. Track & tag LLM bot traffic separately

Use reverse DNS, headers, ASNs to tag sessions from AI crawlers and populate your CRM.

Tools like FireGEO can help, or build your own tracking via reverse DNS + ASN logs.

Track the early numbers to see if these paths convert better. Intent should be high because they asked a precise question and got pointed your way.

6. Entity consistency + internal linking

Strengthen pages already cited by AI (find them via audits) with internal links. Models trust what’s already referenced.

Add clear entity markers (brand + city + category) in schema/titles.

One audit showed 3x-6x visibility lifts after tightening entity consistency.

What’s working for you?

Getting quoted in Perplexity/Grok/ChatGPT? Reddit loops working? Or what’s still tricky? Share with us!

+ PS: (We have a small marketing hacks group for portfolio founders, DM with a growth insight if you’d like in.)

++ as always if you’re raising email us deals@array.vc or DM me!

+++ Market Map of companies tackling GEO

[Array VC] 15 Themes We’re Most Excited to Back

Shruti Gandhi — Fri, 09 Jan 2026 15:36:27 GMT

Array Ventures invests $250k-$3m checks at formation. If you are starting a company in AI Infrastructure, making any industry such as healthcare, finance, manufacturing, supply chain, etc. better. Email us at deals@array.vc.

At Array Ventures, we launched our AI Labs to actively build, experiment, and learn alongside the founders we back. In just six months, we’ve generated over 500,000 lines of code developing internal tools and running hands-on experiments. The lab allows us to rapidly test new ideas, evaluate emerging products, and deeply understand the realities of building with AI.

When companies pitch to us, we don’t just review decks, we use the products. If a company is pre-product, we can often relate directly to the underlying challenges through our own building experience. In many cases, we attempt to recreate parts of a product ourselves to understand the technical complexity, tradeoffs, and whether alternative approaches or workarounds exist.

There are many compelling areas to invest in AI, but our focus is shaped by the challenges we encounter firsthand in the lab, as well as the needs our portfolio companies consistently raise. These experiences guide where we believe the AI stack still needs meaningful improvement.

Below are the areas we are most excited to invest in at Array Ventures today. If you’re building in or adjacent to any of these spaces, we’d love to connect. We are actively investing and can review pitches within 48 hours.

Self-driving operators: “AI suggests” to “AI does”
AI Governance Infrastructure: Control Layer Systems
AI Economics Infrastructure: Do more with less
Edge Intelligence: Inference, Optimization, Efficiency
Embodied World Models: Physical AI
Symbolic AI: Deterministic Reasoning
Knowledge-infused AI: Context Management
Energy Infrastructure: Hardware Bottleneck
Life Operators: Personal companion
Agent Economy: Transaction and commerce
Verifiable AI: On-Chain Proofs
Agent Learning Systems: RL and Training Loops
Vertical AI: Make any industry efficient
Content Authenticity: AI Manipulation
Boring Email Company: Just make my Inbox better :)

Thanks

Array Ventures Team

Our content is getting interesting everyday with our AI experiments. You can get those updates in between these quarterly updates on X and LinkedIn.

Is M&A the new acceptable IPO?

Shruti Gandhi — Mon, 05 Jan 2026 18:21:06 GMT

The most striking feature of 2025’s deal activity is the overwhelming dominance of M&A transactions at $478B, up 74% from 2024 M&A activity. M&A in 2025 were defensive moves driven by fear of being left behind by:.

Being structurally late to AI: Building internally was slower than acquiring.
Losing pricing power: As AI commoditizes features, owning differentiated data, workflows, or distribution becomes essential to defending margins.
Talent scarcity at the frontier: Elite AI and security teams remain incredibly hard to hire. Acquisitions are one of the few ways to secure them at scale.

Google’s $32 billion acquisition of Wiz stands out as a watershed moment for what it signals about enterprise security’s strategic importance.

Similarly, IBM’s with its $11 billion Confluent acquisition and $6.4 billion HashiCorp deal and Meta <> Manus deal demonstrates how legacy tech giants are buying their way into modern infrastructure markets to add agentic orchestration and full stack workflows.

Nvidia’s $20 billion acquisition of Groq and Meta’s $14B by ScaleAI illustrates another trend: the blurring lines between traditional deal structures. This hybrid approach suggests that companies are getting creative with deal mechanics to navigate regulatory scrutiny while still achieving strategic objectives in the hot AI chip market.

More IPOs in 2026

2025 had a few IPOs: CoreWeave ($30B), SailPoint ($13.2B), Circle ($6.9B), Figma ($19B), Chime ($11B).

The companies that did go public represent interesting case studies. CoreWeave’s success reflects the insatiable demand for AI infrastructure, while Circle’s IPO validates the maturation of crypto infrastructure beyond speculative tokens.

While IPOs aren’t dead and we will see a lot more of them in 2026, large M&A deals are leading to faster liquidity options for founders and investors. The traditional VC investor journey from investment to IPO is not the only path to liquidity. The more accurate framing is that we’re entering an era of exit optionality. The best companies have multiple paths to liquidity, and the choice between M&A and IPO increasingly depends on market timing, strategic fit, and founder preferences rather than one universally superior option.

Array Ventures: What lies ahead!

Shruti Gandhi — Tue, 30 Dec 2025 21:16:03 GMT

Array Ventures invests $250 - $2.5M in companies at inception helping with Day 0 to Series A journey.
Email us your decks at deals@array.vc

2025 is a wrap and excited for what’s coming in 2026! 2025 was full of milestones from launching our new website array.vc to our Array AI Lab, to making 9 new investments, 5 follow-on investments!

16 of our companies raised capital this year and we have added great new VC partners such as Accel, IVP, Menlo Ventures, and A16Z to our follow-on investor community.

We just keep building along side our founders! We have added 500k lines of code that’s from 41k just a couple quarters ago!

Our X and LinkedIn followers have also grown (Thank You community!) Feedback we get is people like our honest take on what we are building and sharing so we will keep doing that in 2026.

All of this wouldn’t be possible without our amazing founders so very grateful for their trust and partnership!

Our year in review wrapped up in this image!

Try our office hours agent, Joyce, we launch on Thanksgiving to learn about our investments and Array in general! She is working 24x7!

Call Array Ventures for Office Hours

If you’re building something in AI, email us at deals@array.vc — we’re actively investing $250K–$2M right now.

🫶 Best Wishes for 2026 🫶

Array Ventures Team

Our content is getting interesting everyday with our AI experiments. You can get those updates in between these quarterly updates on X and LinkedIn.

Array Ventures Office Hours: Grateful For You!

Shruti Gandhi — Thu, 27 Nov 2025 15:28:37 GMT

Today we’re excited to launch the beta of our 24×7 “Office Hours with Array Ventures,” powered by the Array AI Labs.
Meet Joyce — our AI analyst you can call anytime for a voice-based office hours session. She’s working for you even when we’re asleep!

Call Array Ventures for Office Hours

If you’re building something in AI, email us at deals@array.vc — we’re actively investing $250K–$2M right now.

I’m incredibly grateful to everyone who has helped me on my journey. I’ve been wanting to give back to more founders than I can meet with personally, so this Thanksgiving we tried an experiment: we cloned me (Shruti) to create Joyce, using insights from thousands of our conversations. Joyce knows most of what I know about startups and about what we like to invest in at Array Ventures.

Joyce can help answer questions about:
• What we look for in companies
• GTM strategy
• Our areas of focus
• General industry or fundraising questions

With Joyce, you don’t have to wait for replies to emails, LinkedIn, or X messages — you can get help on what you’re wrestling with right away.

At Array, we respond to pitch submissions within 24–48 hours, but Joyce can give you early guidance instantly.

Important note: We’re builders and love experimenting with the latest models, so Joyce may hallucinate or be imperfect. She’s still in beta — please forgive any rough edges! But we finally feel ready to launch a voice experience that’s both high-quality and affordable.

And yes, we’re working through Thanksgiving week. We’re eager to meet great AI founders. (Last Black Friday, we invested in Wabi — a few weeks later they raised a $20M round led by a16z!) We’d love for our next investment to come from this week as well.

Stay subscribed — more launches coming soon!

[Array VC] AI Experiments, Market Observations, New Investments, & Job Opportunities

Shruti Gandhi — Thu, 20 Nov 2025 15:09:37 GMT

Array Ventures (website) invests in companies at inception helping them in their journey from Day 0 to Series A. We have a highly successful track record of graduating companies to top-tier VCs. We can lead or follow with check sizes of $2m or less.
Email us your decks at deals@array.vc and we will follow-up within 48 hours with our decision.

If you are good at content creation on X, Instagram, TikTok then we want to talk to you! We are hiring at Array VC for these skills. Please apply here if you are a fit.

Summary In Video: Our team at our virtual office in SF :)

New Investments and News

Wabi gave a shoutout to Array for being their first investor! They announced their $20m round from A16Z. Here is the launch announcement from 2 weeks ago and their X launch is here.
Runable can automate your daily tasks. Their launch got over 1 million views
Listen to breaking healthcare data bottleneck talk by Integral CEO where he talks about how Integral automates HIPAA expert determination and data preparation with configurable AI agents.
FinanceOps talk about how they automate A/R Automation with empathy.
HappyRobot has a new office and an incredible new partnership with DHL!
See how Zingly is winning the CX transformation battle
Meibel shows how enterprises can move beyond demos and deploy generative AI with runtime confidence: live scoring, policy-based routing, and full decision traceability. See one of their talks at the AI Conference.
Flamingo raises $2.2M to automate MSP operations with AI open source platform
CandorIQ helps optimize your workforce spend
Precanto is transforming FP&A and closing good customers!
Feeling nervous about posting online? Automate your LinkedIn / X marketing with confidence with Blaze

Jobs

All the jobs at our portfolio companies are on our website. Many of our companies are looking for social media marketers, content marketers, Chief of Staff, Ops, AE’s, etc. Check it out!

Array AI Labs

We have been brewing a few projects at our AI Lab.

Content

We have been able to create a lot of good content with our new AI Labs UGC Tools template. Our update video was generated with a workflow created using AI models - NanoBanana, Seeddream, 11Labs, InfiniteTalk, and Qwen.

Deal Evaluation

We use AI to aggregate information on all deals and surface insights early. Hence we are able to process 300+ deals in less than 48hrs.

We used Wokelo.ai for some part of competitive research and Runable to schedule repetitive tasks for this project.

Testing: As technical builders, we are coding every day. We are also able to try products in our own developer environment and test products during diligence. Founders have been impressed with our technical skills so feel free to share what you are building and we will take it for a spin!

Array In The Wild

Most recently I was speaking at AllRaise about AI Startup Investing with Erica Brescia from Redpoint and it was very exciting because Gweneth Paltrow and Dr. Jill Biden spoke right there right before me!! It was a great inspiring summit.

Hanging out with the Eventual Computing Team before Ray Summit.

Threw an event with our portfolio company, Meibel.ai, around AI conference.

Hacked together a last minute breakfast with Hannah Grey at the SF Tech Week.

Trivia of the day: Yann LeCun is leaving Meta to start an AI company. How much do you think he will raise? His comps are Fei Fei Li who raised $230m for World Labs, Mira Murati raised $2B for Thinking Labs and currently raising more at $50-60B valuation next, and Ilya Sutskever who raised $2B for SSI.

🫶 See ya until then 🫶

Array Ventures Team

Our content is getting interesting everyday with our AI experiments. You can get those updates in between these quarterly updates on X and LinkedIn.

[Array VC] AI Experiments, Market Observations, New Investments, & Job Opportunities

Shruti Gandhi — Thu, 04 Sep 2025 13:44:17 GMT

Array Ventures (website) invests in companies at inception helping them in their journey from Day 0 to Series A. We have a highly successful track record of graduating companies to top-tier VCs. We can lead or follow with check sizes of $2m or less.
Email us your decks at deals@array.vc and we will follow-up within 48 hours with our decision.

Array AI Lab Experiments

We launched Array AI Lab last quarter and have added many experiments to tell you our opinion on the latest models and companies. Excited to share this newest experiment where I got to be an AI Model with help of other model friends Nano Banana from Google Gemini 2.5 + Kling 2.1 + Seedance 1.0

We unveiled a redesigned array.vc website and logo, vibecoded using Lovable and V0 by Vercel built by us. You can follow us on X or LinkedIn to stay on top of our experiments.

Exit

Congrats to Opsverse on being acquired by StackGen . Excited for them to continue to grow.

New Investments and News

Congrats to HappyRobot for announcing their $44M Series B in this video.
Join the community at OpenMSP to discover opensource alternatives for your tech stack.
MeibelAI raised $7M round to be the runtime platform to build confident agents. Here are their thoughts on structurable data.
Checkout the launch of AI research platform PerspectiveAI on producthunt.
Brands can license Pinterest content seamlessly with partnership with Catch+Release.
Data quality affects your revenue growth and Openprise is here to help you.
Gartner recognized Uniform as top vendor on their magic quadrant for Digital Experience Platform.
Watch out for Blendid’s next-generation robot in Walmart, City Sports, UCLA, and Mayo Clinic next.
Eventual Computing announced their $30M raise for their data processing engine that works across all modalities voice, audio, and video.
BlazeAI can create your marketing posts to generate demand for your business!
Check out LastApp’s campaign on tiktok/insta.

Jobs

If you are good at content creation on X, reddit, tiktok then we want to talk to you! We are hiring at Array.vc for these skills and so are some of our fast growing startups!

All the jobs at our portfolio companies are on our website. Many of our companies are looking for social media marketers, content marketers, Chief of Staff, Ops, AE’s, etc. Check it out!

GTM On My Mind

Traditional media coverage of seed fundraises has diminished since reporters simply don’t have the resources to cover every round. As a result, startups are finding new ways to capture attention. What’s interesting is that these efforts aren’t just about visibility; they’re also generating customers and revenue from the outset. Marketing is becoming a core growth motion from Day 1.

Consider Cluely, they kicked off the trend with a viral launch video on X. Their first campaign drew 13M views with the provocative tagline “cheat on everything” despite little clarity on their product. Within four months, they secured a Series A from a16z and followed up with billboard campaigns in Times Square.

Since then, the trend has accelerated. Just this week, astrology startup Arcarae released a vague launch video that reached 7.3M views in a single day. AnswersAI marketing videos have certainly cracked this virality with 90m views!

Meanwhile, companies like Replit and Lovable have tapped into X and the vibecoding movement to scale to $100M+ ARR in under a year often with remarkably lean teams.

Skeptics question the sustainability of this growth. But these are real revenues at a scale and speed not seen before. While churn rates are higher, the ability to capture substantial revenue early provides both resources and confidence to refine strategy. In many cases, this rapid path to revenue is proving more compelling than traditional enterprise growth models.

I am DYING to share some of our portfolio company launches for Runable, Wabi, LastApp, and Flamingo soon! Sign up on their waitlists if you want to hear from them directly!

🫶 See ya until then 🫶

Array Ventures Team

I try to send this newsletter once a quarter. For updates between newsletters follow me on Twitter and LinkedIn. Constructive feedback always welcome!

Launching Array AI Labs at Array Ventures

Shruti Gandhi — Fri, 30 May 2025 16:27:17 GMT

At Array Ventures, as a technical firm we’re constantly experimenting with the latest AI developments. It sparks ideas on how we can better support our founders with go-to-market strategies and product innovation.

Email us deals@array.vc if you are starting a company. We are investing in all new AI advancements displacing every industry

Launching Array AI Labs at Array Ventures where we experiment with the latest AI tools. Founders love working with us because we are builders ourselves and the lab is a place we will try things in open. I have been dying to share what we have been building with you!

Recently, we’ve been building some internal AI tools, and one experiment came from a pain point I had while running the [Array] podcast a few years ago. We had some incredible guests who shared unique insights but I often found myself thinking, “Haven’t they said this elsewhere?” With so much content already out there, I started wondering if we really needed to take up their time to get the same information again.

So when Notebook LM launched, a lightbulb went off: What if I could solve two problems at once?

Relaunch the podcast without a heavy lift on production
Capture expert insights without requiring time from the guest

And so, the AI-generated podcast experiment was born!

Check out this auto-generated interview with celebrity investor Ashton Kutcher, where he shares what he looks for before making an investment. We’ve also created similar interviews featuring thought leaders like Garry Tan (Y Combinator), Bill Gurley (Benchmark), Reid Hoffman (LinkedIn), and Patrick Collison (Stripe). You can find them all at: https://array.vc/array-ai-lab

Big thanks to the amazing tools that made this possible: Google Veo3, Hedra_labs, ElevenLabs, RunwayML, Kling.ai, HeyGen, Synthesia, and of course, Python.

We repurposed publicly available content for this project—hopefully our guests won’t mind being part of this AI experiment!

Stay subscribed to see more of such launches!

Zoho's Revolutionary Path: Challenging Silicon Valley's Conventional Wisdom

Shruti Gandhi — Tue, 22 Apr 2025 18:44:00 GMT

Zoho’s success story of building a global software company with $1B+ in revenue without any VC $$.

Zoho now employs over 12,000 people globally serving 80+ million users across 180+ countries. The founder Vembu’s net worth exceeds $5.8B while maintaining 88% ownership.

I came across a fascinating breakdown of Zoho’s unconventional business approach that deserves more attention.

While tech giants follow the standard playbook—recruit from top universities, raise massive venture funding, and optimize for rapid growth—Zoho has quietly built a billion-dollar global business by doing the exact opposite.

Their revolutionary talent strategy:

Recruiting directly after high school through Zoho Schools
Paying students stipends during practical training
Focusing on skills over credentials

The result? Nearly 20% of their engineers have no formal degrees yet build world-class software used by millions globally. These team members often solve problems more creatively because they’re trained to think practically rather than academically.

Their business approach proved exceptional during COVID:

When venture-backed competitors conducted mass layoffs, Zoho:

Maintained full employment
Accelerated hiring
Launched free tools to help struggling businesses transition to remote work

The secret? Their bootstrapped model eliminated pressure from investors or debt obligations, allowing decisions based solely on long-term viability and customer value.

Perhaps most inspirational is founder Sridhar Vembu, who despite his $5.8B net worth, lives in a rural village, rejecting material excess and finding contentment in simplicity.

Today, Zoho serves 80+ million users across 180+ countries, employs over 12,000 people globally, and generates $1B+ in revenue—all while Vembu maintains 88% ownership.

In a world obsessed with unicorns and hypergrowth, Zoho reminds us there’s another path to building enduring, impactful businesses.

Summary:

Zoho Schools recruits students after high school, pays them during training, and hires them for actual projects, focusing on practical skills over theory.

The Infrastructure Behind AI's 'App Layer'

Shruti Gandhi — Thu, 13 Mar 2025 15:39:28 GMT

In today’s AI investment landscape, there’s endless buzz about the “app layer” - those shiny, user-facing applications promising to revolutionize everything from content creation to customer service. But as someone deeply embedded in this space, I’ve noticed a critical misunderstanding: most so-called “app layer” investments are actually infrastructure plays in disguise - or worse, just fancy UIs without substantial technology underneath.

What Is the “App Layer” Anyway?

When investors talk about the “AI app layer,” they’re typically referring to the end-user applications built on top of foundation models. Think ChatGPT’s interface, Midjourney’s image generator, or any number of AI-powered productivity tools. These are the touchpoints users interact with directly.

But here’s the crucial insight many miss: in the current AI landscape, the real differentiation rarely happens at this superficial level.

Why Most “App Layer” Investing Is Actually Infrastructure Investing

The truth is that most truly valuable “app layer” companies are building critical infrastructure components disguised as applications. Let me break this down:

1. Data Processing Pipelines

Many AI applications that appear simple on the surface are actually complex data processing systems underneath. They’re not just pretty interfaces to LLMs - they’re building sophisticated data ingestion, transformation, and management systems. This is infrastructure, not application.

2. Fine-tuning and Model Adaptation

Companies that claim to build “AI apps” often spend most of their engineering resources on adapting, fine-tuning, or creating specialized models for their domain. This isn’t app development in the traditional sense - it’s infrastructure development that enables the app to function.

3. Integration Frameworks

The most valuable AI applications aren’t standalone tools but systems that integrate deeply with existing workflows and data sources. Building these integration frameworks is infrastructure work, not application development.

4. Domain-Specific Optimizations

When an “app layer” company delivers superior performance in a specific domain, it’s almost always because they’ve built custom infrastructure optimized for that domain’s requirements - not because they have a better UI.

The Two True Categories of “App Layer” Investments

Once we strip away the marketing speak, there are really only two categories of what people call “app layer” investments:

1. True Infrastructure Plays

These companies are building the picks and shovels of the AI gold rush: specialized data processing systems, model optimization frameworks, integration platforms, and domain-specific AI infrastructure. Their user interfaces are simply windows into this infrastructure.

2. Visual Wrappers (or Vertical SaaS with AI Features)

The second category consists of companies that are primarily building traditional software with AI features added as a competitive advantage. These are effectively vertical SaaS plays with an AI twist, that still need heavy infrastructure development.

The next time you hear about an exciting new “AI app layer” investment opportunity, look beneath the surface. In today’s AI landscape, sustainable value creation happens primarily at the infrastructure layer, even when it’s packaged as an end-user application. The truly transformative companies aren’t just building interfaces to AI - they’re building the specialized infrastructure that makes AI truly valuable in specific domains.

Check out our app layer companies such as HappyRobot Placer.ai Rad AI Terrantic Wokelo AI and many others that you might call the app layer company but invest heavily in the infrastructure behind it.

Reach out to us arraydeals@array.vc if you are building an infrastructure-first app layer company :) We can be your first investment and get you to build a stable company that raises a strong Series A!

[Array VC] Exciting Reads, Investments, & Job Opportunities

Shruti Gandhi — Thu, 13 Feb 2025 19:01:37 GMT

Array Ventures (website) invests in newly forming data/AI companies. We have a highly successful track record of graduating companies to top-tier VCs. We can lead or follow with check sizes of $1.5m or less.
Email us your decks at arraydeals@array.vc

How Array Ventures Returned Fund I (2016) in 2024—And Why It Matters

In venture capital, liquidity is often an afterthought. Many firms focus on paper returns, but delivering real capital back to LPs is what truly sets top-performing funds apart.

At Array Ventures, the results speak for themselves:

✅ We fully returned our 2016 Fund I in Q1 2024—with plenty more upside still in play.
✅ We’ve distributed capital to LPs every year for the past five years.
✅ More good news 📰 on the DPI 💰 front to report next quarter 👏👏👏

This is no small feat in today’s venture landscape. With unicorns like Databricks, Stripe, SpaceX, Figma, Notion and many other $10B+ value companies are staying private longer, the average time to liquidity now exceeds 14 years. Many funds are sitting on assets with no clear path to distribution.

Average number of years to go public used to be 7-10 years and most the companies listed above are over 11+ years old. The average number of year for companies to go public is well over 14+ years now. Companies that can access capital in the private markets are taking advantage of JOBS Act to remain private. All this is to say that DPI is becoming a larger challenge for many funds but Array VC’s story is that of a contrarian.

Portfolio Company Follow-on Rounds

What you can see with Array’s portfolio is our founders ability to raise follow-on capital from top-tier firms. Last year a third of our portfolio raised follow-on capital and in some cases twice in the same year! Here are some notable ones:

RadAI Series B from Khosla Ventures and Series C from Transformation Capital
HappyRobot Series A from A16Z
Openprise Series B from Morgan Stanley
PlacerAI Series C

Investments

We invested in 7 companies last year and led 5 of those 7 investments. We also made additional 6 follow-on investments in our winners. As our companies succeed they often are growing. Please look at open jobs are these portfolio companies here.

I try to send this newsletter once a quarter. For updates between newsletters follow me on Twitter and LinkedIn. Constructive feedback always welcome!

[Array VC] Exciting Reads, Investments, & Job Opportunities

Shruti Gandhi — Wed, 25 Sep 2024 16:06:09 GMT

Array Ventures invests in data/AI companies in their first ever raise. We are still looking to make new investments in 2024. Email us at arraydeals@array.vc if you know anyone starting a company and looking for $1.5-2M checks.

✉️ Array Ventures Invites

Many of you have been wondering how to invest in our companies. We are starting an Array Ventures Founder Showcase. Our first one is for angel investors next week Oct 2nd at 9:30am PT. Please RSVP here to get an invite to this one or one of the future ones.
If you are around Oct 10th at 5pm in SF during SF Tech Week then come to our data event, From Data to Deployment: Lessons from AI Founders, we are hosting with our portfolio company Eventual Computing. RSVP here.

Array Ventures All Things Enterprise Conference in June was a success! We had over 100 VCs, half of our founders, and many LPs in the room. Four companies raised their follow-on rounds in Q3 from meeting some VCs at the conference. 🎉🎉🎉

One of the popular sessions was from one of Array Ventures early founder Noam Ben-Zvi of Placer.ai. You can watch his session on his 0 to $100M ARR journey here 🎥.

📰 Array Ventures Mentions

We’ve been fortunate to be in the press last couple quarters:

Interview on Bloomberg News on AI investing
Profile on Array VC portfolio on Business Insider
We are on the 19 SuperForecasters in VC list
Business Insider also added Array VC on Top 100 Seed VCs and Top 40 Women Investors lists

Portfolio Notable News & Follow-on Rounds

Investors, Job Seekers, Curious People: List of our companies

PlacerAI raised a quick internal round of $75m at $1.5B and one of our LPs who met the founder at the annual meeting participated as well!
Solugen secured a conditional $213M loan from DOE. This is a big deal as it’s a similar loan that Tesla secured in 2010.
Overview.ai just sold it’s product to 100th factory!
Capsule launched Video Motion Design Systems to help enterprise teams create on-brand video at scale.
Circle Logistics has done 100k AI calls leveraging HappyRobot.ai that builds AI Voice Agents to automate phone calls in logistics.
Wokelo.ai generates reports for any industry in a few minutes! Some fascinating findings in their reports on online gambling and GLP-1 drugs!
CandorIQ offers Global Benchmarking Data across 100 countries, 5 million records & 380 roles.
Blumira received awards solidifying its position as a cybersecurity innovator.
Zingly.ai had a good launch and also added CMO and CRO to their team.
Uniform is getting love from the Content Management System community for their composable architecture and ease of use of their product.
CastAgent.ai highlights early indicators of success for a SaaS company.
Goodtime.io is named in the Gartner’s Hype Cycle for Interview Scheduling.
Terrantic announces their seed round raise!
BigCompany goes behind the scenes of how some big brands leverage SMS.
AnswersAI hit 100M organic views in 1 month!
RadAI announces partnership with Google and closes their Series B.
Eventual Computing (data warehouse for unstructured data) launched DAFT after announcing their raise from CRV.
Tumble.to granted patent for distributed networked laundry machine control
Productiv adds Sidekick to help you manage your software licenses.
L Catterton, a leading consumer investment firm, partners with LiftLab
Catch an interview with CEO of Catch+Release.

With all this great news it’s clear our founders have been busy over the summer! We have also been busy and have made a few stealth investments. We will announce them in the next year end newsletter!

Job Opportunities At Array’s 65+ Portfolio Companies

Our companies are hiring and looking for Full Stack Engineers, AEs, SDRs, Marketers, and more globally including many remote openings. Check out all the listings here and please share it with your talented friends.

Array Ventures in the World

We had a successful CPO, CRO, CHRO, CFO gathering to add some great operators to our community. We have been calling this series “B2B Leaders You Should Know” and we had great attendance from senior leaders from Zoominfo, Adobe, Chewy, and many others. We did this one in collaboration with our companies CandorIQ, Precanto, and CastAgent.ai

Appreciate you reading this far! We will now go back to looking at new deals, helping our portfolio companies, and doing other VC things!

Also, I try to send this newsletter once a quarter. For updates between newsletters follow me on Twitter and LinkedIn. Share this newsletter with your friends or reply with their email to add them to the distribution. Let me know if you find this valuable and any other things you would like to see!

[Array VC] Exciting Reads, Investments, & Job Opportunities

Shruti Gandhi — Thu, 21 Mar 2024 15:04:58 GMT

2024 started with some great news for Array Ventures. We returned most of the Fund I to our LPs in 7 years. 🎉🎉🎉
Some notable companies in this fund: PlacerAI, RadAI, Solugen, Openprise Catch+Release, Zendar, and Vue.ai.

Array Ventures (website) invests in enterprise data/AI companies in their first ever raise. We are still investing connect with us (arraydeals@array.vc) if you are know anyone starting an enterprise data/AI company and looking for a $1.5 - 2m check

Welcome New Investments to the Array Family in 2024

73rd Investment: Moksa AI is a video intelligence platform identifying theft, shoplifting, & employee efficiency.
74th Investment: AnswersAI is a 1-click answers to questions

Investors, Job Seekers, Curious People:
Here is a list of all our relevant companies

Portfolio Notable News & Follow-on Rounds:

Openprise (RevOps data automation) closed a Series B led by Morgan Stanley
RadAI announces partnership with Google and closes their Series B
Eventual Computing (data warehouse for unstructured data) launched DAFT which is seeing a lot of traction!
Happyrobot builds AI Voice Agents to automate phone calls in logistics
Tumble.to granted patent for distributed networked laundry machine control
Productiv adds Sidekick to help you manage your software licenses
L Catterton, a leading consumer investment firm, partners with LiftLab
CandorIQ offers Global Benchmarking Data across 100 countries, 5 million records & 380 roles

***Are you still investing? Are you an angel or seed investor interested in seeing deals then please fill out this form to get access to B2B data deals. ***

Job Opportunities At Array’s 60 Portfolio Companies

Our companies are hiring and looking for Engineers (leads and IC’s), Sales, Customer Success, Marketers, Designers and more globally including many remote openings. Check out all the listings here.

Market Observations From An Early Stage Startup Investor

2023 was a tumultuous year with Q4 being the roughest year in terms of fundraising for companies I have seen in my decade of venture career. VCs were tired from a rough year, unable to have a differentiated opinion and ready to check out. Customers wanted to push out all decisions to Q1, and many companies who have been barely surviving from multiple cuts needed money to keep the lights on but had already made all the cuts possible.

The quiet dying of startups will continue to happen in 2024. But many of those founders are coming back with new AI ideas, more enthusiasm, and even larger rounds. VC’s came back with a more renewed excitement with a reminder of why they got into the VC business. Customers are also in a similar boat and back to spending and purchasing. Public markets have also been showing strong performance and even crypto seems to be back!

In summary, the VCs are active again at all stages. Valuations in AI companies are still very high across all stages. The bet VCs are making is this is a once in a lifetime opportunity like the early days of the internet where new companies being built today will be the next Big Magniﬁcent 7 company.

The deal ﬂow has picked up again this quarter compared to Q4 last year. We are back in situations where rounds are oversubscribed with multiple term sheets. We are lucky founders are choosing to work with Array Ventures.

Appreciate you reading this far! We will now go back to looking at new deals, helping our portfolio companies, and doing other VC things!

[Array VC] Exciting Reads, Industry Updates, and Investment & Job Opportunities

Shruti Gandhi — Wed, 06 Dec 2023 15:48:26 GMT

Array Ventures (website) invests in enterprise data/AI companies in their first ever raise. These tend to be companies raising a round for the first time and in many cases just incorporating as we commit to investing in them.

***Are you still investing? Are you an angel or seed investor interested in seeing deals then please fill out this form to get access to B2B data deals. ***

Welcome New Investments to the Array Family

Tellen - Audit Workflow
Stealth - AI Customer Experience

We are still investing connect with us (arraydeals@array.vc) if you are know anyone starting a B2B data/AI company.

State of the Exits:

A Fund 2 company PrecisionGX was acquired by Trend Health. This is the third Fund 2 acquisition. First 2 were by Era Software acquisition by ServiceNow in 2022 and Tank Utility acquisition by Generec in 2021.
Fund 1 didn’t have any exits in Q3 but it has 8 exits so far from amazing enterprise public company logos such as Pulse by Gartner, Art19 by Amazon, PassageAI by ServiceNow, Simility by Paypal, Zecops by JAMF and two others Wootric and Lennd by PE backed companies.

Portfolio Notable News & Follow-on Rounds:

Overview announces OV20i an AI-enabled All-in-one vision inspection system
Openprise introduces DataOps for RevOps
RadAI wins AuntMinnie’s best New Radiology Software award for 2023
EmpInfo is now the preferred income and employment verification solution for UKG Ready customers
Capsule introduces AI-powered video editor for enterprises
Blumira wins “SIEM Solution of the Year” in 2023 Cybersecurity Breakthrough Awards Program
GraniteRock, Georgia-Pacific, CalPortland awarded Environmental Team of the year at Mapistry Annual Summit
Cast.app launches AMA feature for the quick information on your business
Gartner recognizes OpsVerse as a representative vendor in the Market Guide for Internal Developer Portals
Uniform’s New Enterprise Visual Workspace Unifies Content, Data, AI and Technology in a Single Cloud for Marketers
Fedex announces an investment in Vue.ai
Zendar announces partnership with NXP Semiconductors along with their $30M raise.
Oro Labs closed a $34M Series B round led by Felicis Ventures

*Few others that haven’t been announced yet but you will hear about it soon!*

Job Opportunities At Array’s 58 Portfolio Companies

Our companies are hiring and looking for Engineers (leads and IC’s), Sales, Customer Success, Marketers, Designers and more globally including many remote openings. Check out all the listings here.

Market Observations From An Early Stage Startup Investor

The startup funding landscape in 2023 has been characterized by a significant slowdown compared to previous years, with total funding down by around 42% compared to 2022. There are a number of factors such as the rising interest rates, geopolitical tension, and economic uncertainty that have contributed to the slowdown in startup funding in 2023. The slowdown in startup funding has had a significant impact on the startup ecosystem. Many startups are struggling to raise capital, which is forcing them to cut costs and lay off employees.

Despite the overall slowdown, there are still some startups that are able to raise large amounts of capital. These are typically startups that are addressing large and growing markets such as AI, Climate tech, and Healthcare. Startups in these verticals have managed to raise and monopolized the funding dollars. This has led to a situation that some have described as “feast or famine,” with some startups still able to raise large amounts of capital while others are struggling to secure any funding at all. Larger funds are still sitting on record-high levels of dry powder ($280B in Q2’23) and are eager to deploy them, but they are looking for higher quality companies with valuations at rounds that are attractive for today’s venture market conditions.

Here are the high-level trends we see in the market. The general thesis is that the larger firms will retreat to their traditional funding stages that they play in which would bring sanity to the early stage market.

- Seed is Shrinking: In Q3’23 we see the first significant QoQ dip in deal sizes and valuations, at both the top-decile and median seed rounds. Up until now, the seed market has been propped up by multi-stage firms entering the category. Multi-stage firms were involved in 36% of all seed deals in 2022. We are beginning to see the first signs of those multi stage investors leaving seed in pursuit of later stage deals. Nonetheless, valuations will remain high until we see the supply of seed capital provided by multi-stage firms decrease substantially over the next few quarters.

- Slight Uptick for Late-Stage Investors: Late-stage venture funding on a deal value basis has ticked upwards slightly on a year-on-year basis in Q3. However, overall deal count is still declining. This has been largely due to one major deal: Anthropic’s $4B round with Amazon. We are hearing that investors are increasingly shifting their strategy towards later-stage rounds where the market conditions are in their favor.

- Slight Opening in IPO Market: The IPO market has shown signs of opening up, albeit modestly. Both Instacart and Klaviyo listed at lower share prices than their previous VC round, despite having revenue growth and being profitable. These listings illustrate some of the challenges that even best-in-class companies face if a listing is their next financing option. Current multiples are well below where many companies raised during 2020-2021, which means that companies often have to face an IPO listing at a lower valuation hurdle than their last round.

- Growing Corporate Venture Capital: Corporate venture capital activity has increased as a proportion of overall VC deal value, surging to 63%. This suggests that CVCs are investing dollars and we have seen new CVC’s start new funds as well.

Thank you for reading. As always, please reach out with any questions. Wish you a joyful holiday season.

[Array Ventures] Exciting Reads, Industry Updates, & Jobs Opportunities

Shruti Gandhi — Wed, 09 Aug 2023 14:10:20 GMT

Array Ventures (website) is a preseed investor in enterprise companies solving hard problems in AI, Data, Security, Infra, Cloud, and select vertical. Array VC was on the Seed 30 VC list published by Business Insider! Connect with us (arraydeals@array.vc) if you are thinking of starting a B2B data/AI company.

Welcome new investments to the Array Family

Expanso - Distributed data processing
Happyrobot - Vision-Language models for image analysis (current YC S23)
CandorIQ - Compensation and Headcount Planning (current YC S23)
Wokelo - Business Research and Analysis

Portfolio Notable Follow-on Rounds

Release Management for mobile apps company Runway raises $2m from Bedrock Capital
M12 invests in Bytewax to build the future of stream processing
Zingly raises from Scribble Ventures to 3x customer sales pipeline
Blumira announces Series B Funding along with their XDR platform launch
Catch+Release raises Series A for brands to license user-generated content using AI
Vue.ai raises Series C from Avatar Growth to boost their reach into new verticals

*Few others that haven’t been announced yet but you will hear about it soon!*

Job Opportunities at Array’s 54 Portfolio Companies

Our companies are hiring and looking for Engineers (leads and IC’s), Sales, Customer Success, Marketers, Designers and more globally including many remote openings. Check out all the listings here.

Our companies have some fun news as well. See what they have carefully put out there for you:

Wokelo.ai is developing valuable business research tools for investors to run their funds
OpsVerse announces Aiden, a Generative-AI Secure DevOps Copilot
Veteran finance leaders found a company, Precanto, to use AI for real-time headcount planning
Capsule AI’s video editor for enterprise launched in private beta with companies like Hubspot, Pinterest, and BCG (watch their cool demo)
Data platform, Mozart Data, announces free tier for startups
Integral launches product to Maximize Dataset Customization and Privacy
Funtivity by Hermis, an engagement and learning platform, was highlighted by Microsoft CEO, Satya Nadella, during his keynote
Eventual Computing launches Daft a high-performance distributed dataframe library for multimodal data
Stronghold Launches StrongholdNET with merchant rewards and DeFi-backed financing
Almanac interviews 5000 business leaders to create “The Modern Work Method,” to help professionals work better
Blendid’s Robotic Kiosks at Walmart, Bay Club, and Grady Memorial Hospital Shake Up the Food Industry

Market Observations from a Preseed Investor

Understanding how the startup funding market is doing is on top of everyone’s mind. On a recent panel at ServiceNow I try to give a sense of that to the founders. Shared some of my thoughts on this post. Quick observations are:

VC Funding - While it looks like AI startups are funded easily today that is only true for fresh new preseed startups and not 1-2 years old startups that might be fundraising. Overall venture funding in Q2 was at its lowest quarterly total in more than 3 years. Later stage investors are very picky about what they invest in. While there were investments in some late stage AI startups like Anthropic and Cohere, some recent AI investments Stability AI and Jasper have already been experiencing some trouble in less than a year after some large raises. Majority of the later stage VCs are still waiting to make any big bets with meaningful ownership. What they are doing instead is investing at the seed stage and giving incorrect signals to founders by investing in rounds with high valuations.

Tech IPOs - There have been no notable tech IPOs since Q4 2021. There was a decent non-tech IPO of Cava. (I had their food last December in DC and I thought it was pretty good!)

M&A - There has been some tech M&A activity of companies such as MosaicML (Databricks for $1.3B), Casetext(Thomson Reuters $600m), and Mode Analytics (Thoughtspot $200m). Although the overall numbers are still low. While many had predicted M&A activity to pick up unfortunately high interest rates makes borrowing for the acquirer too expensive. The sentiment is that companies may not want to acquihire since good talent is available to hire in the market with recent layoffs.

If you made it this far then thank you for reading. You might also enjoy this post on Taylor Swift. I like to hear from you as well. Please feel free to respond with your favorite AI story!

How to define a vision for your startup?

Shruti Gandhi — Thu, 04 May 2023 17:22:40 GMT

I often speak to founders today who think their vision is to take down a large company in their category. That’s not a vision but a personal motivator. A mission statement explains why the company exists, and a vision statement explains where it is headed.

A company’s vision statement should be focused on its long-term goals, purpose, and values, rather than just taking down a competitor. A good vision statement should communicate the company’s long-term aspirations, the problem it aims to solve, and the impact it wants to make.

This type of statement is more likely to inspire & motivate employees, stakeholders, & customers & guide the company towards sustainable success.

Having a vision statement for a startup is important for several reasons:

Provides direction and focus: A clear and compelling vision statement helps the startup define its long-term goals and direction, and provides focus to the team, helping them stay aligned and motivated.
Guides decision-making: A well-defined vision statement guides the startup’s decision-making process, helping the team make choices that are consistent with the company’s long-term goals and values.
Attracts customers and investors: A strong vision statement communicates the startup’s purpose and value proposition to potential customers and investors, helping the company attract the right partners and resources to achieve its goals.
Builds brand identity and culture: A vision statement can serve as the foundation for a startup’s brand identity and culture, providing a shared sense of purpose and values that can guide the company’s branding, marketing, and hiring decisions.
Measures progress: A vision statement can also serve as a yardstick for measuring the startup’s progress and success, helping the team assess whether they are making progress toward their long-term goals and adjust their strategy and tactics accordingly.

Overall, a vision statement is an essential component of a startup’s strategic planning process, and helps the company stay focused, aligned, and motivated as it works to achieve its long-term goals.

Few vision statements for enterprise startups:

Slack: “To make people’s working lives simpler, more pleasant, and more productive.”
Dropbox: “To unleash the world’s creative energy by designing a more enlightened way of working.”
Zoom: “To make video communications frictionless and secure, enabling people to interact as if they were in the same room.”
Atlassian: “To unleash the potential in every team, by creating tools that help teams work smarter and faster.”
Twilio: “To fuel the future of communications by enabling developers to build the applications that will power the way we communicate.”
Stripe: “To increase the GDP of the internet.”
PagerDuty: “To empower teams to take the right action, when seconds matter.”
Asana: “To help humanity thrive by enabling all teams to work together effortlessly.”
Rubrik: “To simplify the complexity of IT by enabling enterprises to manage, govern, and protect their data.”
Snowflake: “To enable every organization to be data-driven, by providing a platform that enables all data users to gain insight from all their data.”

Here are some for AI companies:

OpenAI: “To ensure that artificial intelligence benefits all of humanity.”
NVIDIA: “To accelerate the discovery and deployment of AI to solve the world’s most challenging problems.”
UiPath: “To democratize RPA and deliver a robot for every person.”
Cognitivescale: “To augment human decision-making with the power of AI.”
Vicarious: “To build unified algorithms of human cognition that can be used to solve real-world problems.”
DataRobot: “To empower every organization to unleash the power of AI and become an AI-driven enterprise.”
Algorithmia: “To make AI accessible to everyone by creating a marketplace for algorithms and models.”
Hugging Face: “To democratize AI and make it accessible to everyone, everywhere.”

Few more from consumer companies:

Amazon: “To be Earth’s most customer-centric company, where customers can find and discover anything they might want to buy online.”
Tesla: “To accelerate the world’s transition to sustainable energy.”
Microsoft: “To empower every person and every organization on the planet to achieve more.”
Nike: “To bring inspiration and innovation to every athlete in the world.”
Starbucks: “To inspire and nurture the human spirit – one person, one cup and one neighborhood at a time.”
Google: “To organize the world’s information and make it universally accessible and useful.”
Patagonia: “Build the best product, cause no unnecessary harm, use business to inspire and implement solutions to the environmental crisis.”
Coca-Cola: “To refresh the world in mind, body and spirit, and inspire moments of optimism through our brands and actions.”
LinkedIn: “To create economic opportunity for every member of the global workforce.”
Airbnb: “To create a world where anyone can belong anywhere.”

You don’t need to wait to define your vision after you are bigger. It is something that is intrinsically why you should want to start that company. These early vision statements demonstrate the startups’ focus on solving a particular problem or providing a unique value proposition to their customers. They are aspirational, concise, and reflect the company’s mission and purpose. Over time, as the startups grew and evolved, their vision statements may have been refined or expanded to reflect their changing goals and priorities.

LP Update: Navigating AI, VC, Fundraising Today

Shruti Gandhi — Thu, 20 Apr 2023 15:35:50 GMT

I am sharing part of our LP update that you might find useful if you are a founder navigating the current fundraising environment.

Since our fund has always focused on data and AI we dedicate some time discussing AI trends and fundraising in this AI-first world.

We invest upto $1.5m in preseed AI/data companies. Reach out to us at arraydeals@array.vc if you are starting a company.

AI Update:

Companies in the AI category are either infrastructure (tools, models, etc.) or applications (such as health, finance, legal, etc.). Some other hot companies in these categories that just keep raising in the last few months (some even multiple times): Stability AI, Jasper, Hugging Face, OpenAI, Midjourney, Character.ai, Anthropic, Clari, Weights and Biases, Synthesia, Harvey, Replit, Runway, LangChain. and many others. This Forbes 50 AI list is a good start. Here is a good visual way to see the company broken down by categories.

Large companies are also trying to be part of this AI story now especially as you might have been reading about Microsoft (OpenAI), Google (Bard), and now Amazon’s latest news with Bedrock. More will definitely come.

These advances in AI are happening really fast. Autonomous agents like Auto-GPT and BabyAGI are demonstrating the race to get ahead in AI is just getting faster. While the results can be inconsistent there is still a lot of work to be done here and new areas ripe for innovation/investment. The announcements about ChatGPT4 were literally on that first Monday after the SVB weekend leaving no time to catch a breath. The influx of deals, working with existing companies on taking advantage of the power of ChatGPT, and thinking about the new opportunities to invest in have certainly kept me busy.

Travel has picked up and so has the number of events and hackathons. While my last 2 investments are not in the bay area (they are in Europe and Seattle) it is still the place founders want to move to / visit to build their AI company. I was at an Hugging Face AI event at the Exploratorium in SF with 5k people a few weeks ago! They were calling it the “Woodstock of AI”.

Pre-Seed Market Trends:

1) Fundraising at pre-seed is still very heated for pre-seed in all the areas we invest in - AI/Data/Infra. If you want a general primer on the AI/ML/GenAI trends today here is a good article that can give you a good background.

2) Valuations and round sizes should have come down but they haven’t. Deals and the deal speed have still not slowed down. Deals are still oversubscribed in days. There was a short window in Q4 where it seemed like the pace was slowing down but it picked up again in Q1. Average valuations from what I am seeing for a mediocre team has gotten even worse than previous years.

3) There has been a growing trend of solo founders who want to raise and grow their team after the raise.

4) Many undifferentiated companies are being created just on OpenAI but are still getting funded if it is a good team or sometimes by just a group of syndicate investors. It would be wise to say everyone is figuring it out.

Follow-on rounds:

True (priced) follow-on rounds are very rare unless you are one of the hot companies in the categories such at AI and then every firm wants to pile money in these companies. You might be seeing a lot of buzz in any companies in the AI space across all stages.

While some of our companies are raising priced follow-on rounds what is more common these days is companies are raising many millions on just SAFE in follow-on rounds. We generally do not mark up these SAFE rounds. Over half of our active portfolio companies have raised follow-on capital in SAFEs to increase runway. Investors are not looking for much of a bargain/down rounds just yet. Since there is still a lot of money in the market the down rounds are not the norm just yet but they are coming. Flat rounds are happening more frequently over down rounds. You have to remember though flat rounds are still a reasonably good valuation since the rounds raised even a year ago were already very frothy.

While many funds are trying to invest in the AI space, there are a few interesting things to note.

Many of the same funds are going into almost all of the same companies with overlapping investments.
Many of the companies are also getting marked up by their own investors or the same pool of investors.
Many companies do not have significant revenue
Many companies do not have any differentiation
Lastly, a growing trend is open source projects gaining fast traction and raising venture capital dollars.

What I am telling our portfolio companies?

AI First: As I mentioned above, I am working with companies on aligning them with the new AI trends and taking advantage of it. Some founders are making serious efforts to integrate AI in their narrative and differentiate.
Solve for a real painpoint: Align their product as must have vs nice to have for customers to really want to buy their products. Cutting spend is real across the board and growing pain from adoption of microservices over the last few years is becoming visible. Customers are showing signs of bundling and buying vertically integrated products.
Cash Management: It would be ideal if that happened from growth and customer adoption of the startups which our startups are certainly pushing for but I am also helping them think through burn and cash planning with our companies to give them over 12 months and ideally 24 months of runway. Some of our companies are achieving good revenue milestones as well so that’s been positive as well.

Please let me know if you found this update helpful. You can also find some tweets and LinkedIn posts from me to see some real-time updates if you like on these topics.

Team Dynamics for Preseed Round

Shruti Gandhi — Thu, 21 Apr 2022 21:53:29 GMT

I’ve been seeing solo founders raise preseed rounds ($4/5m) to then hire their co-founders and teams. Many of these only connect with the purpose of starting a company and do not have a prior relationship.

I have also seen more founder breakups within first 2 years which demoralizes & derails the company. Leaves messy cap tables. Really hard things to recover from.

Starting a successful company is not like taking a successful job. There are ups and downs & you mostly have to stick it out for years figuring things out without guaranteed success at below market wages for much higher potential long term upside.

It’s rough at a startup. You have to figure out a lot. Problems aren’t handed to you. You have to find them on your own. Solve them on your own. You have no money to hire people to solve things for you. There is a lot to do. You have no idea what’s going to make it a success.

Sometimes it feels easy to take capital first and then figure it all out later. Figuring it out after you take money is too late. You’ve taken money, made commitments, hired people, and honestly given up better opportunities where you could have been more successful.

It takes a while to figure out how to build a trusting co-founder working relationship with someone. Figuring that out while building a startup just sounds very painful.

Array Bytes: Pitch Deck Insights

Shruti Gandhi — Thu, 03 Mar 2022 19:28:43 GMT

Sometimes I like to read pitch decks backward, because most companies bury important information about what they do & their teams at the end.

They spend so many slides explaining the pain point, business, and market.

We like to recommend 3T’s to focus on when crafting your story.

So what should your deck cover? “3Ts - Team, Traction, and Tech”

Team

Are the founder’s experts in the space?
Do they have a unique take on the space?
How well do founders know their competitive landscape?

Traction

Highlight any traction
Customer logos
Verticals your customers are in - Do you have a focused vertical or you are going after a few?
Share customer quotes and stories on why they chose your solution over others

Tech

Explain your tech

Is it hard to build?
What are some differentiating components?
Do you have experience building something in the space before?
Why couldn’t you build it a few years ago?

Things about TAM, pain points, etc are just build-up in your deck. Don’t spend many slides on those. Get into your story asap. Focus on highlighting why you are so special.

In today’s market, every category is crowded and companies need ways to stand out based on their 3Ts. These 3T’s are about you, make them stand out!

What kind of investors should you pitch to?

Find investors who come prepared and wanting to know more, not educating themselves just from your pitch. Even if an investor who doesn’t know your space exactly, but is active and genuinely interested would want to know 3Ts before digging into the detail.

Lastly, don’t spend a ridiculous amount of time working on your deck. It’s not the deck that will get you funding but how you present it. This brings me to my next item for fundraising - Narrative.

Follow me on Twitter (@atShruti) or subscribe to my newsletter (https://shrutigandhi.substack.com/) to read more on that soon!

Exciting Array Ventures Updates, Exits, Jobs, and Links

Shruti Gandhi — Thu, 28 Oct 2021 16:13:03 GMT

Array Ventures (website) invests $1M checks in pre-seed stage B2B companies. We invest across the enterprise stack with our thesis of Intelligent Enterprise. Connect with us if you are thinking of starting an enterprise software company. We are still looking to invest in 2-3 companies before end of 2021!

Exits!! :)

Congrats to 2 of our portfolio companies on their acquisition by Generac (Tank Utility) and Classy (Lennd). Within the last 5 years we have had 8 exits and invested in a total of 58 companies between 2 funds. 5 of those exits have been in the last year! We have returned 31% of our 1st fund which launched in 2016 and feel proud of our accomplishments.

Happy Fall!! 🍂 🍁 - There is an easter egg 🥚🐇 in this newsletter 📰! See if you can find it.

Job Opportunities at Array Ventures:

We are looking to bring on a Principal and Head of Community and/or a Chief of Staff onto our team. As you can tell from the updates above Array is growing along with our portfolio and the new team member will allow us to take our ambitions to the next level.

Principal (VC) - Please apply here.
Head of Community and/or a Chief of Staff - Please apply here.

Fund News:

Check out what Shruti shares with Kia Kokalitcheva on Axios about Enterprise software’s reawakening.
Shruti shares her investor perspective on managing a tech startup during covid at Mozart Data’s first conference called Symphony No. 1.
Shruti puts together a list of Megatron Investors that invest in startups valued over $1B+.
Here is another podcast where Shruti shares her thoughts on how to network and build a career in VC.
Shruti shares her thoughts with SVB on Amplifying Performance with Diversity in VC.

Welcome New Investments to the Array Family:

Hermis - Enabling virtual employee engagement
DevOpsNow - Fully configured DevOps tools deployable in minutes to run on any public or private cloud
Stealth - Customer support platform

Portfolio Notable Follow-on Rounds:

Our companies have also been busy with some good follow-on raises. We have been an investor since their first ever raise in all these companies.

Solugen - $350M Series C led by Singapore GIC
Almanac - $34M Series A led by Tiger Global
Openprise - $16M Series A led by Susquehanna
Blumira - $10M Series A led by Mercury Fund
Blendid - $2M crowdfunding raise bringing total raise to $20m

Job Opportunities at our 58 Portfolio Companies:

Our companies are hiring and looking for Engineers (leads and IC’s), Sales, Customer Success, and more globally including many remote openings. Check out all the listings here.

Enterprise in Motion:

If you ever needed reassurance on the viability of enterprise products then check out these things that happened in enterprise this quarter:

13 enterprise companies IPO’ed in Q3 with a collective $86 billion dollars in valuation at their time of IPO. Overall Enterprise software represents nearly $530 billion, growing 9.1% from the previous year. In Q3 the general market saw a 3% gain compared to BVP’s Cloud index that had an 8% return. Public enterprise companies are growing and continue to show the value enterprise businesses provide to their customers with the avg. revenue growth rate of 32%.

Other Updates from around the web:

4 things VC’s get wrong about investing in AI (but Array doesn’t)
While the use of APIs is growing so is the security risk. Web application attacks tripled in 2021 and 88.72% of the attacks used common API vulnerabilities.
Two Chinese streamers sold about $3B worth of goods in a half-day livestream.
Using deepfake-like tech and location-based services Cadbury worked with one of the highest paid celebrity Shahrukh Khan to create a personalized ad for each viewer!

If you made it this far then thank you for reading. I like to hear from you as well. Please feel free to respond with your favorite market insight stories!

Share this newsletter with your friends or reply with their email to add them to the distribution. First 10 people to share this newsletter on Twitter or Linkedin (tag me) can get a copy of The Informed Company: How to Build a Cloud-Based Data Stack to Explore and Understand Data a book written by my friend Dave Fowler, CEO of Chartio/ Atlassian. Let me know if you find this valuable and any other things you would like to see!

Also, I try to send this newsletter once a quarter. For updates between newsletters follow me on Twitter and Substack.

The Megatrons — $1B+ Valuation Investors

Shruti Gandhi — Thu, 16 Sep 2021 19:45:13 GMT

A few years ago it was a founders dream to get a $1B valuation - Ultimate Unicorn status. In recent years that is becoming a less exclusive of a club. According to CB Insights there are a total of 817 Unicorns and 418 of them are in United States.

There is another massive trend going on where large funds who I call the Megatrons are coming together to invest in $1B+ companies and getting them to $10B, $30B, and in some cases $100B valuations pre-IPO(Stripe valued at $95B).

Megatron is a leader whose goal is to rule the universe and destroy everyone in his path. Not unlike many of these funds who take out competition but massively funding the market leader. So I found it appropriate to call these investors Megatrons.

Now that our fund Array Ventures is privileged enough to have companies with unicorn status my founders are asking me about investors who invest in companies valued beyond $1B. Who are these investors who can do that and value your company at $10B or $40B (recent Canva valuation!)

So I started putting together a list. Maybe there are many more investors I have missed but please send the names my way so I can include them. Maybe just like the rapidly growing unicorns this list might also get unmanageable but let me attempt to put this together. Here are some current Megatron funds that have been actively leading these rocketship rounds:

I have organized them in the order of how close to $1B vs $50B valuation they can invest.

Tiger Global — https://www.crunchbase.com/organization/tiger-global
Tiger needs no introduction as they have been investing in a range of valuations even some starting at Series A including an Array Ventures Series A company.
Softbank — https://www.crunchbase.com/organization/softbank
Similar to Tiger, Softbank has also been investing at all stages such as their recent Series C investment in Sendoso and of course many other $1B+ investments we have seen over the years.
Sapphire Ventures — https://techcrunch.com/2021/09/13/jumpcloud-raises-159m-on-2-56b-valuation-for-cloud-directory-tool
Sapphire recently invested in JumpCloud at $2.5B valuation and they have certainly invested in Array Venture’s Series B stage company, Safegraph.
Addition — https://www.crunchbase.com/organization/addition-7af4
A new entrant with spin out from Lee Fixel who used to be at Tiger Global has led a few deals across the “growth” spectrum as well. They certainly also start early such as Series A as well.
IVP — https://www.crunchbase.com/organization/institutional-venture-partners
More of the earlier side of $1B investment rather than later but certainly growth stage. They invested in Array Ventures company Series C round of Productiv.
Insight Venture Partners — https://www.crunchbase.com/organization/insight-partners
Insight manages over $26B and invests across all stages but if you can believe it their 1st fund was $25m. To all emerging managers this is a great case study for us.
Goldman Sachs — https://www.crunchbase.com/organization/goldman-sachs
Goldman has been a traditional multistage Series B+ to IPO investor including investing early in Uber.
Iconiq Capital — https://www.crunchbase.com/organization/iconiq-capital
Fund that manages money for many Silicon Valley billionaires such as Zuckerberg has been investing across all stages also starting from Series B.
Singapore GIC — https://www.crunchbase.com/organization/gic
They are one of the more serius later stage investors and led Series C for Solugen which is one of Array Venture’s portfolio company.
Temasak Holdings — https://www.crunchbase.com/organization/temasek
Temasak also invested in Solugen
General Atlantic — https://www.crunchbase.com/organization/general-atlantic
T. Rowe Price — https://www.crunchbase.com/organization/t-rowe-price
Recently marked up Canva to $40B and Gusto to $10B.
Dragoneer — https://www.crunchbase.com/organization/dragoneer-investment-group
Looks like they just led Discord’s $500m round at $15B valuation
Wellington - https://www.crunchbase.com/organization/wellington-management

Some other mentions such as Hedge Funds, Private Equity Funds, and Investment Firms who are also Megatron investors especially if it fits their specific thesis. Many of these can invest closer to IPO.

Franklin Tempelton — https://www.crunchbase.com/organization/franklin-templeton-investments
Bond Capital — https://www.crunchbase.com/organization/bond-57ec
Fidelity — https://www.crunchbase.com/organization/fidelity-management-and-research-company
Altimeter Capital — https://www.crunchbase.com/organization/altimeter-capital
BlackRock — https://www.crunchbase.com/organization/blackrock
Capital Group — https://www.crunchbase.com/organization/capital-group
Silver Lake — https://www.crunchbase.com/organization/silver-lake
Lone Pine - https://www.crunchbase.com/organization/lone-pine-capital

There are a series of traditional VC firms have also stepped up to invest across multiple stages of companies including ones that are valued over $1B. They still do traditional early stage investing but have also raised large Growth Funds to invest all across the later stages. My sense is currently they invest closer to $1–5B valuations vs. $50B.

General Catalyst
Founders Fund
Sequoia
Andreessen Horowitz
Social Capital
Lightspeed
Maverick Ventures

Hope the unicorn founders find this list valuable. Please feel free to comment or email me (hello@array.vc) to add more names to the list. No promises!

For more on this topic subscribe to our newsletter here. If you found it valuable re-share it here on linkedin and also on twitter.

Exciting Array Ventures Updates, Exits, & Job Opportunities

Shruti Gandhi — Tue, 10 Aug 2021 14:51:47 GMT

Exits!! :)

Congrats to 2 of our portfolio companies on their acquisition by Amazon (Art19) and Gartner (not public information). Within the last 5 years we have had 6 exits and a total of 55 companies between 2 funds. We have returned 31% of our 1st fund which launched in 2016. Compared to many other pre-seed funds from 2016 vintage we rank high on our metrics. We are in the top 1% for returns and loss ratio numbers. We are proud of our accomplishments and heads down execution.

Welcome new investments to the Array Family:

Bytewax - Serverless platform for serving ML models in real-time
Tumble - Smart laundry solution for commercial buildings.
Sliceup - SliceUp is an automated platform for log data wrangling & ETL.
Stealth - Release Management

Portfolio Notable Follow-on Rounds:

Our companies have also been busy with some good follow-on raises. Few others that we can share yet but you will read about it in the next newsletter!

Xwing - $40M led by Blackhorn Ventures
Placer - $50M led by Buckley Ventures and Fifth Wall
GoodTime - $9.5M Series A led by KTB Ventures
Productiv - $45M Series C led by IVP

Job Opportunities at our 55 Portfolio Companies:

Our companies are hiring and looking for multiple roles across all departments and globally including many remote openings. Check out all the listings here.

Fund Updates:

We launched a few initiatives to collaborate with the best folks in enterprise.

Expert Network: We launched an expert network and we have a ton of amazing operators that have signed up. If you want to help a B2B startup, please sign up here.
Angel Network: We also have deals going out to people that have signed up for the angel network. If you are an enterprise angel investor then fill out your information here to see some highly vetted exclusive deals that we are also investing in.
Angel Fund: Our parallel fund 2 for angels was oversubscribed and we have already invested in 6 deals and few more on the horizon. Based on the success of this fund we will launch another one alongside Fund 3 next year.
Check out this video from SVB highlighting some advice from me for GPs raising their first fund.
Find my AMA (Ask me Anything) on starting high growth companies on Elpha here.
Stay tuned for more programs that will come out Array Ventures!

If you made it this far then thank you for reading. I like hearing from you as well. Please feel free to respond with your favorite market insight stories!

Also, I try to send this newsletter once a quarter. For updates between newsletters follow me on Twitter. Share this newsletter with your friends or reply with their email to add them to the distribution. Let me know if you find this valuable and any other things you would like to see!

Activate your Investors: Monthly Investor Updates in 5 Bullets

Shruti Gandhi — Tue, 13 Apr 2021 18:09:04 GMT

According to a recent study, companies that regularly communicate with their investors are twice as likely to raise follow on funding. I have a concept called “activating” your investors.

Founders spend so much time picking the ideal investors for their round. They also spend a lot of time trying to get intro to all the right investors. If the company is lucky to have been oversubscribed then they spend a lot of time picking the perfect mix of investors for the round.

After the round closes, oftentimes it’s the virtual crickets in terms of investor communication. Most founders don’t know how to activate their investors. The excitement and the high from a new investment wears off and the investors think you don’t need them beyond the money which is often not true.

In the early days, companies spend a lot of time trying to look for intros to design partners and customers. The chances that your curated investor and advisor list having a warm connection to many of these customers is very high.

You should regularly update your investors monthly since this keeps you accountable and also gives you a chance to engage them with a particular ask or advice on a pressing issue that can have a 10x impact on your business.

How to structure the updates in 5 bullets?

How’s it going? Any major things to note? Churn, Big wins, what’s working / not working
Company Dashboard: What are you tracking? MRR, Engagement, Burn, Money in bank (Runway)? When is your next raise?
Your next milestone: 30 customers in 3 months, $1m ARR in 6 months, 10 new hires, etc.
Help you need to get there:

Strategic: Pricing, upsell, etc. or Intros to customers, open job roles (always share a link), etc.
Ideal Customer Profile — List of Companies & Roles of people you want introductions to. Kinds of companies you want introductions to — size, sector, certain tech stack, etc.
Blurb: Your new company blurb to share with potential intros.

5. Upcoming press and Investor call to action — retweet, share, blurb to use, etc.

Series B: Placer.ai sends weekly aggregated new customer emails to investors.

From the CEO — This style of updates has resulted in 100+ intros over time, because investors are engaged, and they see the examples, and “have ideas”.
- Noam Ben-Zvi, CEO of Placer.ai

Series Seed: RadAI sends weekly milestone emails with new customer contracts and upsells
Series Seed: Mapistry sends all sorts of impressive metrics and charts in their monthly updates.
Series Seed: Openprise sends monthly financials along with target revenue vs. actual review every month.

“I get sprinkle of feedback. It also forces me to think about what aspects of the business investors maybe interested in learning more about.”
— Ed King, CEO of Openprise

Series A: PulseQA shares a version of their deck from the board meeting

“Someone always writes back and does intros. Keeps us honest and transparent. And including the team on it also keeps them accountable”
- Mayank Mehta, CEO of Pulse.qa

Series Seed: Capsule shares an updated version of their investment memo on notion. I love this as if someone were you invest at that exact moment there is a lot of clarity on how the company comes across to their audience.

Common Concerns with putting together updates:

I am busy building a company and I will get around to updating investors.
I am worried the update might get shared around and leak our inner workings.
I’m not killing it right now. I’ll wait till I have something positive to share.
It’s a lot of work and I rather focus on the company.
I have a board now and those early investors are a bit out of touch.

I can address these one by one but in summary I can tell you that the benefits outweigh the concerns. This short 5 line template takes away the “I am too busy” argument and no investors don’t just want to hear from you when things are going well. Investors want to know if they could have helped you when things were not going well and you asked for help so at least they were aware of it. Asking for help makes you look stronger and confident in your ability to leverage your network to succeed.

*** If you are that worried about your updates being shared share them over docsend. ***

I also tell founders that even if you fail this is one way you can have your investors back you again for your next venture.

Think of the investor update as a checkpoint for your startup journey as writing the update can be both humbling and exciting. Building a startup can be a lonely journey and keeping your investors in the loop on a consistent basis will make sure you are always part of a team that wants you and more importantly wants to help you succeed.

Check out the tweetstorm here. Also, follow me here to get future posts.

All Things B2B Summit

Shruti Gandhi — Thu, 18 Feb 2021 13:45:44 GMT

I am hosting our annual Array Ventures Summit on Feb 25th from 11-1:30pm Pacific time, with a remarkable lineup of some of today’s leading investors & founders who will share their thoughts on #AllThingsB2B.

RSVP here to attend and access content post event.

Attendees will get an exclusive look at what top-tier B2B founders from companies worth billions such as DataBricks ($28B), DataRobot ($3B), Drawbridge (acquired by LinkedIn) have to say about the Role of Data in Intelligent Enterprise.

In addition, premier VCs from top-tier firms such as Kleiner Perkins, Greylock, Wing Ventures will discuss what they look for in enterprise companies and share their thoughts for the future of enterprise. Here is the agenda for the summit:

RSVP TO ATTEND

If you are starting or thinking of a B2B company leveraging data and AI then email us.

Array Ventures is a B2B SaaS early stage fund where we invest across the enterprise stack, infrastructure, middleware, and applications, with our thesis around “Agitated Workforce” and “Intelligent Enterprises”.

What is an Intelligent Enterprise?

Intelligent Enterprise is the future of data and AI. Businesses require automation to succeed at scale. We need to rebuild the entire tech stack to bring intelligence to their products, process, and workflow. The next Salesforce, Workday, Stripe, Hubspot, Okta or Zendesk will change the way an industry works just like these billion dollar enterprise companies have. They will look to rapidly turn data into insight that will help them become market leaders.

Check out some of Array Ventures Intelligent Enterprise companies…

…take a look at our entire portfolio companies here

Who Are the Agitated Founders?

“Agitated Founders’’ find themselves using outdated or cumbersome tools and become passionate about changing that status quo. They use this passion to turn that idea into their own brand. We empower these founders & have an amazing community of successful B2B founders & investors willing to help. Just check out our summit speakers who are part of the Array Network.

Where We Like to Invest

Array likes to lead companies with ~$1m check as their first backer i.e help founders from the ground up often even before company formation to get to a meaningful traction and then to the follow-on raise. We call it the 0-1-10M ARR journey. We have done this successfully for over 70% of our companies :)

What we look for in founders we like to invest

Differentiated point of view on their industry
Mission-driven
Builders
Closers
Differentiated access to talent
Curious, hustler, problem solvers

(I’ll share more thoughts on these factors via my upcoming Substack posts. Subscribe here)

We live & breath data, AI, B2B and SaaS. Thinking of starting a company in these areas? Apply to our intimate office hours here. Reach out to us if you are dreaming of starting B2B companies

The All Things B2B Summit

I’m so excited to be able to bring this event to you all. 5 years in, I feel privileged to have access to such talented people who are willing to give their time and share their learnings as part of the Array Network. I feel lucky to do what I do & am excited to wake up and help businesses be efficient. I’ve been at a few companies & I know how agitated I was so let me help you turn your agitation into billion dollar businesses. Email us at arraydeals at array dot vc.

Don’t forget to REGISTER HERE.

11 Startup Opportunities in Enterprise

Shruti Gandhi — Thu, 17 Dec 2020 17:14:55 GMT

When March 2020 came around no one had any idea what the future would hold. Instead, it came with almost $200 billion in deals, record high tech stocks, mega deals, SPACs, and huge IPOs.

Covid has been a catalyst to enterprise adoption of tech such as cloud, security, collaboration, and artificial intelligence that we expected to see in the future.

We are entering 2021 with a little more clarity after the haze from the fires of 2020. Not just with a visibility into Covid-19 vaccines but also new administration in the US.

Biden administration will more of less be more favorable to the big tech and innovation. They are more favorable to immigration and will lax current laws to important talent for US companies so we will see how this impacts the remote work trend.

Here are some high level investment themes we are closely watching as we head into the new year. If you are a technical founding team working on some of these solutions then please get in touch with us.

Lot of these are horizontal ideas that work across industries. Our investments won’t be limited to these areas and we are also open to some vertical industry specific ideas as well.

1. General AI Tools

Companies that help AI developers be more efficient. This is still a large opportunity and the AI adoption in enterprise is just in its infancy.

2. Enterprise Compliance

More startups need to go through security and compliance checks such as SOC2 and HIPAA before they can work with their customers or go through M&A. We are looking to make a bet in specific thesis here.

3. Procurement

Enterprise buying motion is changing. Decision making is shifting to disperse teams with ad hoc buying patterns. New tools around global and local vendor management, data around things like vendor product showcasing, supplier / buyer onboarding, etc.

We have recently made a stealth investment in this space but excited to do more.

4. API Management

With the rise of microservices there is a need for better management, discovery, security, search of APIs across companies and with their customers.

5. Product Discovery

Corporates are inundated with startup requests. We are looking for a way to manage and facilitate the process of startup discovery for large companies.

6. Dynamic Access Management

Managing application by application access and dynamic access as necessary is the next gen of data and identity management.

7. Metered Pricing / Value-based Pricing

We believe the current billing tools don’t work well with the next gen of usage based pricing companies.

8. Email and Application Security

Next gen of tools around phishing, spam, fraud, etc.

9. Data Tools

Companies around data lineage or cataloguing, synthetic data generation, data management.

10. Large Scale Online Transactions

Getting rid of manual invoices and payments even for large transactions. Bringing transparency, trust, and automation across all industries.

11. Marketing and Sales Tools

The one thing that’s clear is companies that nailed marketing during covid won in sales. Enterprise sales was hard without the “wining and dining” and tools that help companies close deals are essential.

We are closing an investment in this space but excited to track for some unique approaches here to help companies close large contracts.

Generally, companies that enable a future we can work in more productively, securely, and collaboratively

Future of work is going to be hybrid with in-person and remote offices but with better collaboration and knowledge management tools. The world has experimented with outsourced teams, local teams, and now we are entering a new wave of experiments with dispersed talent.

There will be a set of solutions and laws that emerge for this unique combination of global vision with a local touch that will provide distributed teams to manage employees from different countries / jurisdictions and the laws that govern respectively. Everything from onboarding, collaboration, performance measurement and employee benefits will be areas where startups can look to build scalable cost effective solutions.

This phenomenon will allow for quality talent to be accessible from anywhere allowing for more focus on building a company culture that fosters employee retention. Hiring remote talent can also allow for a more inclusive and diverse employee base.

Two vertical industries worth mentioning that we are excited about are health and fintech.

If you are starting companies in these categories, haven’t raised capital, and excited to build a fast growing large company then please reach out to Array Ventures. We lead and can follow first check rounds providing value-add on customer development and general go-to-market.

Check out our website and investments here.

*If you agree with these areas of opportunities then please share this article and help reach future founders we can fund to solve these problems.*

Follow me on twitter for more ideas and opportunities.

How To Become A VC From Nothing -

Shruti Gandhi — Tue, 01 Dec 2020 22:46:36 GMT

Last week I reflected on my career. I’m thankful for so many people and opportunities I have received. I didn’t have a traditional path into venture. People often ask me how one gets into venture capital. I’m sharing my experience on how I became a VC from nothing.

Beginnings

I immigrated from a very large city Mumbai to a small town in upstate NY, Poughkeepsie. I didn’t know anyone there except for some extended family. To fund my way to college the advice given to me was to get employable skills for a job, so I taught myself to type & code. I found work at a computing lab at Marist, a local college (and also at a department store).

My work in the lab convinced Marist to accept me without SATs. This gave me the incentive to work hard and graduate early to save the cost of an extra year. I also had time to fit in piano and ballet! I graduated in the recession of 2002. Some professors (my clients at the computing lab) took interest in me & employed me at IBM.

Balancing work and college

Now at 19, I had a 40 hour job as an engineer while in college. I proved to be one of the best Quality Assurance (QA) testers and was one of the rare hires during that recession.

I rose up the ranks at IBM where managers & mentors recognized my efforts & hustle. They rewarded me with the platform to learn business communication, people, & writing skills. They sent me to many executive programs meant to groom ‘the rising stars’. As an immigrant getting this training was a dream.

I wanted to expand my tech skills while working, so I decided to go to Computer Science Grad School at Columbia with a focus on data & analytics. This was a golden opportunity to expand my network so I met everyone I could, including the Head of the CS dept who became my technical mentor and the co-founder of my startup Penseev, a social data platform.

Back at IBM I was working with some high profile teams & projects in the CEO office. You can find Harvard case studies on these groups. The relationships I built there still last to this day and I happen to connect with Amy Hermes from that team who recently invited me on a panel at AWSre:Invent. These friends, bosses, & mentors I had made over 10 years also helped me achieve my dreams of starting a company and going to business school by opening up their networks for me. I wouldn’t have gotten into ChicagoBooth without them.

Business School

At Booth I met my best friends and professors, many of which are Limited Partners (LPs) in my funds. I’m grateful for the faith shown to me considering they meet 800+ students a year and have seen excellent candidates over 25-30 years. The Chicago Booth Magazine also covered my career journey.

Venturing into venture

After my startup, I decided to reverse engineer Venture Capital. Why? The venture world did not have many investors of my profile which I saw as an opportunity rather than an obstacle. So I worked at a few funds during business school where I created a thesis on big opportunities in Big Data, SaaS, and Cloud. I shared my thesis with VCs along with some good potential investments.

One of my professors Steve Kaplan advised me to join Kauffman Fellows and through that network I ended up as one of the founding investors of the Samsung Next Fund. I was one of the only partners with many early exits to @Apple @SamsungUS @McGrawHillK12 where I was lucky to join startups boards & learn from other VCs.

In 2015 armed with operating & VC experience I launched Array Ventures. Many of my early investors were founders, bosses, professors who I had met over 15 years. Founders encouraged me to start Array because they liked working with a technical investor with engineering, operator, & VC experience.

The Array Ventures Fund

Array invests first checks in enterprise deeptech companies where we look to add value on Go-To-Market (GTM) which often means a good path to customers and customer development. During our investment process we meet the team, customers and figure out value add down the road. If we are serious but not ready to invest, we will still help via intros and customer diligence. Our focus is on value add even before the investment.

Now we are on our 2nd fund (3rd coming soon), 45 investments in companies like Productiv, MozartData, Openprise, Blumira, Placer.ai, CasaOne, EraDB, Safegraph, Catch&Release, Uniform, Almanac, Goodtime.io and many more!

We’ve had some good early exits as well with Simility acquired by Paypal (press release here), PassageAI acquired by Servicenow and Hivy / Managedbyq by We Work

We are just getting started! Any founders starting enterprise companies should reach out to us. If you want to invest in Array then there might be an opportunity there as well! I’ve had an exciting 2 decades across 3 different careers and can’t wait to build the next 15 years in venture!

My life lessons that actually have become principles I operate by -

Being grateful is not just an emotion it’s also action. Pay it forward by giving whatever you can without worrying about what you are getting back.
Do everything you can to immerse yourself in your task. If you make up your mind to achieve something give it your all, get skills and experience. Success doesn’t come overnight. For me, after 20 years I am still building my success!
Earn your luck. I’m always grateful to meet my mentors and colleagues who opened doors for me and gave me opportunities but I believe you need to work hard to earn that chance.

Check out the tweetstorm here. Also, follow me here to get future posts.

Finding Deals To Invest — Sourcing

Shruti Gandhi — Tue, 20 Oct 2020 18:33:40 GMT

Best investors often get access to good deal flow. Often that’s referred to as “sourcing” good deals. But the key to sourcing is not about getting a ton of deals your way, it’s also about getting the right kind of dealflow.

What that means is finding deals that -

Fit your investment thesis
Introduce you to a great founding team
Have the potential to scale in big & exciting markets

Building dealflow is not signing up on Angellist or going for networking events. As a new investor, this will be not differentiated and you won’t get a chance to build relationships directly with the founders. Below are few suggestions that would help you better which are:-

Joining the right networks to generate dealflow
Build a thesis as your investment criteria
Attract founders with your value-add as a potential partner/customer

1. Building a network to generate dealflow

You hear about networking as being one of the most important skills in venture capital. Does it mean you are out to events every night? Well yes and no. But mostly no. (You can’t even do that currently in the middle of a pandemic.)

There is a big assumption that a good deal comes from reliable and predictable networks (Google, Facebook, Stanford, etc.)

VCs already know how these networks operate and can reference people building companies from these “known” networks. As a new investor, getting in the middle of the best deal flow coming from these networks would be very important. If you have worked at these companies then you have a head start. Check your alumni networks as sometimes there are alumni angel groups.

Here are some university, company, regional angel groups or entrepreneur networks you can join if you are an alumni. You can find one or create your own-

Company Alumni Groups:

Xoogler — ex-Googler network
Facebook
LinkedIn

University Angel Groups:

UChicago Angel Network
Stanford Angels
MIT Angels with various regional chapters
Columbia Angel Group

General Entrepreneur Groups:

TIE Chapters around the world for south asians
AllRaise for women

These are not exclusive, there are also local groups (e.g. Houston Angel Network) and sector specific groups (e.g. Element 8 investing in cleantech). Think of creative ways to join and find dealflow through these channels

I have also seen new investors pile capital into companies coming out of accelerators and incubators such as Y Combinator and others. They initially invest in companies that come out of these networks and gradually build a relationship with larger networks over time.

2. Use an investment thesis to get specific and quality dealflow

If you are an expert in a specific area, such as procurement, supply chain, manufacturing, dev tools, etc. you may have a strong point of view on areas you want to invest in. This allows you to bring in a unique angle in that space. You can then use this thesis in three ways

Filter and identify startups or founders that fit your point of view making your dealflow more focussed
Create and publish content in your area of expertise. This can attract the right founders get in touch with you.
After you build a convincing thesis as a next step, if you respect some people you think that might be able to build a good company then you can also convince them to leave their jobs and start the company while you can help them seed it. Also, you can help them because of your expertise.

3. Show founders and investors your value is more than writing a cheque

A founder always loves investors and advisors that can help them build their company and help with good customer introductions. Founders love strategic investors who can open doors for them.

If you are in a position to buy products for your company or help founders close new customers with your relationships then you have a great chance of being able to invest in that company.

You can also offer your help to investors and their portfolio companies. More specifically, you can offer to help the VCs during diligence in specific areas of your expertise. Every VC loves to add value-add investors to the captable. Your willingness to help them with diligence and after with the company will definitely entice them to make room for a check from you.

Getting a quality dealflow is more important than quantity. In a fund you typically only have an opportunity to invest in 25-30 deals over a few years. Also, competitive deals are hard to do so you want to make sure you invest in the best company in that category that you can continue to love 5-10 years down the road as well. That is why it’s important to do all this work in generating good dealflow for you.

Also, remember that investing is a long term game and it can’t be transactional. If you start building goodwill things will come back to you in many ways and people will reach out to you and include you in their deals. Good luck investing!

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How to Angel Invest?

Shruti Gandhi — Thu, 10 Sep 2020 18:27:50 GMT

With all the new Securities and Exchange Commission (SEC) regulations around the updated definition of “Accredited Investor” and low interest rates, unpredictable stock market investors are increasingly looking towards investing in private companies. Having access to this new asset class can be exciting. Platforms, such as Angellist, Republic, and many others, make it easier than ever before for any interested individual to become an angel investor.

As a career VC, I have invested across many top tier funds including my own, array.vc. I have accumulated a decade worth of investing experience as both an angel investor and a venture capitalist. I’ve been fortunate to have exits to Fortune 500 companies including Apple, PayPal, and ServiceNow. What I am sharing here is something you should know sooner rather than later. Often investors will invest and assume things and there is a mismatch of expectations.

Answering questions about angel investing often makes my anxiety levels rise, because of how dangerous a game it can be for many people. If you are simply trying to create high returns, but don’t understand the actual mechanics of how an angel invests, you are at risk of losing a lot more than you make. With this post, I am listing things you should consider before you decide you want to invest in startups.

If you have spare change that you don’t mind losing and never seeing it again only then you should consider angel investing. If you do then this post can hopefully help provide some structure and direction in regards to where you should invest it.

Here are some need-to-know basics to get you started:

Asset Allocation:

First, decide how much of your own capital you would want to invest in total to this asset class. What percent of your saving are you willing to lose? Everytime you invest in a company, it’s best to assume you will lose ALL your money, since the majority of companies don’t succeed.

Strategy:

Think about investing in a good number of companies, over the course of a few years. That’s what funds typically do. Since you are most likely going to invest in pre-seed and seed stages, it’s really difficult to predict which companies are going to out-execute the rest and succeed. All your start-ups will seem amazing (otherwise you wouldn’t invest your money and time into them); however, not everyone gets to win in the long run. So, the key is to invest in 15+ companies over 2–3 years and allocate your investments almost equally across those companies.

Exits:

In venture capital, you can’t simply “pull your money out”, unlike some other kinds of investments, like hedge funds.

Even if the company is successful, you may not get your money back until the company exits. Exits, traditionally, only mean 2 things: IPO (going public) and M&A (getting bought by another company either in cash or through stock). The tricky part with stock is that, unless the acquirer is already public, you can only sell it when the private company exits.

Time Horizon:

A large part of angel investing is patience. It takes years before you can have a meaningful exit or before your seed will grow into a fruit bearing plant. Technology companies, on average, take 13 years to go public, assuming things are going well with the company. As we discuss these exit options, there is no way to “take your money out” before these exit events occur. You can’t call it back; you can’t sell the shares when you like (we can go into secondary markets in another post). These are not public shares that have value and can be traded freely. So years after your investment, if you need this money, you can only wait or assume it’s gone. Then, one fine day, years after you forget about it, you might hit a jackpot! …Or you might get an email from a lawyer to sign dissolution documents and no word from the founders.

Dividends:

While there are still some convertible debt instruments where you accrue interest on paper, those are increasingly becoming things of the past. SAFE’s and traditional equity rounds are more common. But, unfortunately, unlike in real estate investment, early stage investments won’t earn dividends.

The best you can hope for is a great return on your investment, a few years after making the deal. The second best is a write off of that investment, but there are never dividends.

Metrics:

The only real indicators of gradual success are if the company sees revenue growth, keeps raising more capital at good terms, and scales the team each round to keep up with the growth.

IRR and other numbers can be interpreted in a lot of ways, but it’s not how private companies really reflect their progress.

You will not get much information on your companies, especially in their first few years. Founders stop giving updates, especially to non majority board members, which generally includes angel investors.

Ownership & Dilution:

Your ownership will become diluted, meaning the number of shares you own of your companies will decrease over time. For example, if you start with 100 shares that represent 1% of the company you can expect it to be around .05% ownership when the company exits, unless you keep investing more, which isn’t always a possibility as an angel investor.

On the bright side, just think of it this way — would you rather own 1% shares of a company going nowhere worth $10M or .05% of a really high growth startup worth a lot more than your original investment maybe around $1B?

Network:

Perhaps you are lucky and find your neighbor’s kid is working on some really awesome company you want to invest in; however, most amazing deals don’t always show up at your door. You have to work on building your network to get good deal flow. On average, VCs meet with thousands of companies each year and only make 5–10 aggregate deals across the firm. The percentage of companies you invest in should be very small compared to how many you look at. If your network isn’t strong, then you might not get a chance to get into good deals.

The Upside Of Angel Investing

The chances of success for startups on average are very low: The success rate is at best 5–8% and that’s on the higher end. Why do even both angel investing then if there are so many risks?

When it works, the returns are really “outsized” and make up for all the other failures in the portfolio. This phenomenon is referred to as power law in venture capital.
The learning along the way can’t be replicated anywhere else. You get to learn about the startup journey of various companies from the ground up as they get built.
You learn about different industries over time.
You get to diversify your investments, after you have invested in the stock market, bonds, real estate, etc.
Most importantly, angels like to invest in companies where they think they can help the founders in their early days and make a profound difference for them.

Although, while angel investing is fun, finding good deals is not easy. And if you find a good deal it’s not guaranteed you can get into the deal. Very few angels can get access to good startups. Rounds are usually very competitive even during this pandemic.

For that reason and many others, I actually recommend most angels put money in venture capital funds. This is a whole another topic I’ll cover in a separate post.

Share this post with your friends who are beginning to think about angel investing.

Subscribe to my newsletter here to learn more about startups, investing, and building a career in venture capital. Feel free to suggest other topics to cover.

Thanks to Jonathan Wolter, Dev Nag, and Gigi Nibbelink for helping me with the edits.

For more on this topic subscribe to our newsletter here. If you found it valuable re-share it here on linkedin and also on twitter.

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