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.

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.

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.

What Is Trending in Tech AI?

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.

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

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

1. Easy to buy, easy to cancel: Simple sign-up makes initial adoption fast but also easy to drop.

2. Tourism Churn: Many downloads or trials reflect curiosity more than long-term commitment.

3. No workflow Integration: Products that don’t embed into core workflows tend to churn quickly.

Companies That Are Winning Do The Following

1. Move upmarket ($250+/month): 70% GRR / 85% NRR—basically matching SaaS

2. Build for habitual workflows (Lovable’s 100k apps/day speaks to this)

3. 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!!

1. 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.

2. Comp your onboarding team on time-to-value.

3. 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.

4. 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.  

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.

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 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.

1. Self-driving operators: “AI suggests” to “AI does”

2. AI Governance Infrastructure: Control Layer Systems

3. AI Economics Infrastructure: Do more with less

4. Edge Intelligence: Inference, Optimization, Efficiency

5. Embodied World Models: Physical AI

6. Symbolic AI: Deterministic Reasoning

7. Knowledge-infused AI: Context Management

8. Energy Infrastructure: Hardware Bottleneck

9. Life Operators: Personal companion

10. Agent Economy: Transaction and commerce

11. Verifiable AI: On-Chain Proofs

12. Agent Learning Systems: RL and Training Loops

13. Vertical AI: Make any industry efficient

14. Content Authenticity: AI Manipulation

15. Boring Email Company: Just make my Inbox better :)

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

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:.

1. Being structurally late to AI: Building internally was slower than acquiring.
   

2. Losing pricing power: As AI commoditizes features, owning differentiated data, workflows, or distribution becomes essential to defending margins.
   

3. 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 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.

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

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 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.

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 (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!

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

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?

1. Relaunch the podcast without a heavy lift on production

2. 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!

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.

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 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 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! 

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!

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 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.

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! 

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! 

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!