It was 2021 and Jonathan Rat was tired of seeing his wife, a dentist, struggle to maintain the tech stack at her practice.

Rat, who had served as a product manager at companies including Uber, Meta and SurveyMonkey, dug into the problem and discovered that “most of the software used in the industry” was more than 20 years old and still required physical services onsite.

“Most lacked integration with other platforms, were slow and buggy, and impossible to train new employees on,” he recalls.

So Rat teamed up with Benjamin Kolin, a former director of engineering at Uber, to start Archy, an AI-powered platform that aims “to put dental practices on autopilot.” The pair previously led the rebuilding of Uber’s payment platform that’s still in use today.

“I realized there was a massive need and opportunity for a modern, cloud-based software platform and set out to build that,” Rat told Crunchbase News. “I also realized bigger tech players have been building software for the larger healthcare market but overlooked the $500 billion dental industry.”

And now, Archy has just raised $20 million in Series B funding to help it grow even more, it told Crunchbase News exclusively. TCV led the financing, which also included participation from Bessemer Venture Partners, CRV, Entrée Capital and 25 practicing dentists who wrote checks as angel investors. The raise brings Archy’s total funding to date to $47 million, Rat said.

The company raised a $15 million Series A led by Entrée Capital almost exactly one year ago. Rat confirmed the Series B was an up round, but declined to disclose Archy’s valuation.

All-in-one tool

Archy claims to replace more than five existing tools to handle scheduling, charting, billing, imaging, insurance, payments, staffing, messaging and reporting “from one login.”

It is now building AI agents “to handle the busywork” such as checking eligibility, filing and following up on claims, writing notes, managing patient communications and scheduling, and “turning raw practice data into clear answers,” according to Rat.

The startup processes more than $100 million in payments annually across 45 states and has seen roughly 300% year-over-year growth, he said. It currently serves 2.5 million patients and has processed over 35 million X-rays through its platform.

The company claims that mid-sized dental practices report saving around 80 hours a month by using its technology, and are able to avoid “big hardware costs.” For example, Rat said that one practice saved about $50,000 in its first year of using Archy.

Dual-revenue model

San Jose, California-based Archy operates on a dual-revenue model that combines subscription-based fees with payment processing services, and offers tiered monthly subscription packages. In addition to its subscription fees, Archy serves as a merchant processor for its clients, generating revenue from a percentage of payment transactions processed through the platform.

“This hybrid approach allows us to remain aligned with our clients’ success while providing flexible options that scale with their business needs,” Rat told Crunchbase News.

The company plans to use its new capital to “hire aggressively” across its engineering, AI and go-to-market teams. Presently, it has 57 employees. It plans to expand internationally starting in 2026.

Austin Levitt, partner at TCV, told Crunchbase News via email that his firm had been looking for a way to invest in the dental space “for a long time” but didn’t find a company that was “appropriately tackling the root of the problem — the core PMS (practice management systems)” until it came across Archy.

He added: “We consistently heard that Archy was supremely easy to use, requiring almost no training in contrast to others, providing a seamless ‘iPhone-like’ experience, and reducing what took 10 clicks in other software to one or none in Archy.”

Related Crunchbase queries:

• Rounds Raised By Startups Using AI
• Venture Funding To Dental-Related Startups

Illustration: Dom Guzman

Every founder knows the thrill of the moment: the first term sheet lands, the product is live, the market is opening up. But in 2025, there’s a new line in the sand: Did you clear the regulatory path before you scaled?

Today, it’s not enough to disrupt the market — you have to anticipate the rule-set that will govern it.

Investors are shifting gears. After a decade of “move fast and break things,” they’re asking: Who built the compliance engine before the crash? Because the truth is, regulation has become a form of alpha — a competitive advantage for startups that think of law not as a hurdle, but as a moat.

The new era of smart compliance

The startup landscape has changed. High-profile failures — from crypto exchanges to wild valuations in fintech and AI — taught us that the regulatory cost of growth can be massive. Today’s investors and founders alike expect legal strategy from day one, not as an afterthought.

Consider the RegTech market: One recent estimate projects it will swell to about $70.64 billion by 2030, growing at a compound annual rate of roughly 23%. Another forecast predicts growth to $70.8 billion by 2033. The message: Companies are no longer asking if they need compliance automation and legal-engineering infrastructure. They’re asking when they can monetize it.

So when a startup designs its product around KYC, AML, data-protection or licensing from the outset, it’s not just avoiding risk — it’s building a moat others will struggle to cross. For founders, regulation isn’t just the cost of entry anymore — it’s the cost of exit-edge.

When the law becomes a moat

There are former unicorns, and there are regulation-ready unicorns. The difference hinges on when they built their compliance architecture, hired legal engineers and treated regulation as product.

Take payment infrastructure: Stripe built payment-security and licensing into its model early, as Stripe’s PCI Level 1 certification and multijurisdiction licenses (U.S. money-transmitter, EU/UK e-money) enabled it to integrate cleanly with Apple Pay, power Shopify’s native payments, and — per a 2023 announcement — expand its role processing payments for Amazon.

Or look at crypto: Coinbase built a licensure footprint early, publishing its U.S. money-transmitter licenses and securing New York’s BitLicense in 2017. Its 2021 SEC S-1 repeatedly frames regulatory compliance and licensing as fundamental to the business.

In insurtech, from the outset, Lemonade hired senior insurance veterans (e.g., former AIG executive Ty Sagalow) and, per its S-1 and subsequent filings, expanded licensure across the U.S., operationalizing the 50-state regulatory landscape rather than trying to route around it.

These examples show a pattern: When compliance is built in from the start, the cost of scaling drops and competitors face much higher entry bars. Regulation becomes a moat — not a burden.

The rise of ‘legal engineering’

Welcome to the era of the legal engineer. The traditional model (sign contract, then lawyer reads, then flagged risk) is being replaced by code, automation and internal teams who speak both product and law.

Startups such as Carta built cap-table software that includes “built-in tools and support to help with compliance year-round,” allowing it to embed governance and securities-law readiness into the product nature of equity management.

Plaid has publicly positioned itself for evolving “data use, access, and consumer permission” rules (e.g., Section 1033) by building features such as data transparency messaging and consent-capture into its API stack — indicating a clear regulatory-first posture in its product roadmap.

And what’s happening in AI? Founders are hiring general counsels on day one to forecast imminent regimes — privacy law (GDPR, CCPA), AI transparency bills, emerging algorithms-as-infrastructure regulation.

The startup battle isn’t simply product vs. product anymore — it’s regulatory architecture vs. regulatory architecture.

Reports back this up: One credible industry estimate shows the global compliance, governance and risk market is already around $80 billion and projected to reach $120 billion in the next five years. In short: Startups that solve compliance at scale are building infrastructure for everyone else to rent. That’s platform-level potential.

Investors are taking note

Regulation-ready startups aren’t just surviving — they’re attracting smarter capital. Venture funds now assess regulatory maturity, legal runway and governance readiness early on. A startup that can show it isn’t “waiting to deal with compliance” but designed it, has a valuation edge.

Crunchbase data shows global startup funding reached $91 billion in Q2 2025, up 11% year over year. While not all of that is focused on law or compliance, the trend signals that smart investors are buried deeper in risk assessment and governance. Legal tech funding is accelerating, too: the sector recently topped $2.4 billion in venture funding this year, an all-time high.

Funds are no longer only assessing TAM or go-to-market speed; they’re asking: “What’s the regulatory runway? Who owns risk? Who built the compliance pipeline?” Because in sectors like fintech, climate tech, health tech and AI, the fastest growth path is often the one that avoids the enforcement arm.

The future: law as competitive advantage

Let’s zoom out for a moment. We’re moving into a world where regulation isn’t a ceiling — it’s scaffolding. It defines markets, enables scaling and filters winners from pretenders. Founders who see law as a source of architecture, not as chewing-gum-on-the-shoe, will be the ones writing the playbook.

Think about AI: Startups that design for regulatory change (data-provenance, audit trails, rights management) are already positioning for the future.

Think about climate tech: Companies that can navigate evolving carbon-credit regimes or ESG disclosure laws are building invisible advantages.

Think about fintech: Those that mastered licensing, KYC/AML, consumer-data flows early are the backbone of infrastructure.

The next wave of unicorns won’t just have better tech — they’ll have truly infinitely better legal DNA. They won’t just disrupt a market; they’ll help write the rules of the market before they scale.

Because in this new era, regulation isn’t a deadweight — it’s a launchpad.

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Aron Solomon is the chief strategy officer for Amplify. He holds a law degree and has taught entrepreneurship at McGill University and the University of Pennsylvania, and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in Newsweek, The Hill, Fast Company, Fortune, Forbes, CBS News, CNBC, USA Today and many other publications. He was nominated for a Pulitzer Prize for his op-ed in The Independent exposing the NFL’s “race-norming” policies.

Related Crunchbase query:

• Legal And Legal Tech Startup Funding, 2025 YTD

Related reading:

• Legal Tech Investment Hits All-Time High With Filevine Funding

Illustration: Dom Guzman

Feyza Haskaraman is joining Felicis Ventures 1 as a partner after several years at Menlo Ventures, Crunchbase News has exclusively learned.

In her new role, Haskaraman will focus on investing in “soon-to-break-out” AI infrastructure, cybersecurity, and applications companies for Felicis, an early-stage firm with $3.9 billion in assets under management.

During her time at Menlo, Haskaraman sourced and led investments in startups including Semgrep, Astrix, Abacus, Parade and CloudTrucks — zeroing in early on how AI is reshaping developer security and enterprise infrastructure.

Haskaraman, an MIT graduate who was born in Turkey, brings an engineering background to her role as an investor. She previously worked as an engineer at various companies at different growth stages, including Analog Devices, Fitbit and Nucleus Scientific. She is also a former McKinsey & Co. consultant who advised multibillion-dollar technology companies and early-stage startups on strategy and operations. It was after working with startups at McKinsey that her interest in venture capital was piqued, and she joined Insight Partners.

Her decision to join Menlo Park, California-based Felicis stems from a shared interest alongside firm founder and managing partner Aydin Senkut to build communities even in “unsexy” industries such as infrastructure and security, she said.

“Whether it’s connecting AI founders or bringing together technical and cybersecurity communities, the mission is the same: Believe in the best founders early and help them go the distance,” she told Crunchbase News.

Felicis is currently investing out of its 10th fund, a $900 million vehicle, its largest yet. More than 60% of its investments out of Fund 9 and 10 (so far) are seed stage; 94% are seed or Series A. In 83% of its investments, Felicis has led or co-led the round.

Nearly $3 out of every $4 that it’s deployed have gone into AI-related companies, including n8n, Supabase, Mercor, Crusoe Energy Systems, Periodic Labs, Runway, Revel, Skild AI, Deep Infra, Browser Use, Evertune, Poolside, Letta and LMArena.

In an interview, Haskaraman shared more about her investment plans at Felicis, as well as why she thinks we’re in the “early innings” with AI. This interview has been edited for clarity and brevity.

Let’s talk more about community-building and why you think it’s so important. 

Over the past few years in the venture ecosystem, just providing the capital is not enough. You need to surround yourself with the best talent. You’re seeing one of the fiercest talent wars in terms of AI talent.

So one of the things that I’ve spent a lot of time on in my VC career is building a community, going back to my MIT roots, surrounding myself with founders, engineers and operators, and also going into specific domains, like cybersecurity — just building a network of CISOs that I communicate with regularly and really support them however I can, and then obviously get their take on the latest technology.

That type of community-building effort is something that Aydin and I will be debating strategy for Felicis as well.

Yes, Aydin (Felicis’ founder) has said that he thinks the next generation of enterprise investors aren’t just picking companies, they’re building ecosystems. Would you agree with that?

Yes, we’re fully aligned on that. First of all, it’s a way of sourcing. Being able to source the best founders involves surrounding yourself in a community of people. You get very close to them, and you want to be the first call when they decide to jump ship and start a business.

As early-connection investors, we want to invest in the founders as early as possible. So that’s why we want to immerse ourselves in these communities that provide prolific grounds for the technical founders that are coming in and building an AI.

You were investing in AI before the big boom took off. Would you say there’s too much hype around the space?

You are correct that there is a lot of euphoria around AI, but if you look at the overall landscape, we haven’t seen a technology that can have such a large impact.

And we’re already seeing the results in enterprises that buyers of these solutions, and consumers of these solutions, including myself and our team, are seeing immense amounts of productivity gains. I remain immensely optimistic about the future and investing in AI, and that’s what we are paid to do, and what I also enjoy as a former engineer.

Are there specific aspects of AI that have you particularly excited?

I personally feel we’re still very much at the early innings. It’s been three years since ChatGPT came out, and the model companies really pushed their products into our lives. But if you take a look at what’s happening now, we have agents that are coordinating and automating our work.

What are ways in which we should be securing agent architecture? And that is also evolving across the board, and if you think about another layer down, like the infrastructure to support these LLMs and agents, I have to ask “What do we need underneath?”

I think there’s a lot more that will come, and there’s a lot of hope for innovation that will happen both across the infrastructure layer, as well as agents. There’s also the issue of “can applications actually be enabled?” I go back to the importance of securing our interactions with the agents and making sure that they’re not abused and misused. It’s a great time to be investing in AI.

What stages are you primarily investing in at Felicis?

We try to go as early as possible. But obviously, given our fund’s size, we have flexibility to invest whenever we see the venture scale returns make sense. But the majority of our investments are seed.

It’s such a competitive investing environment right now. How do you stand out?

Ultimately, what founders value is how you will work with them, your references. They value how you show up in those tough times, how you surround them with talent, how you help them see around the corners. That matters a lot.

I believe that winning boils down to the prior founder experiences that you left, people who can speak highly of you and how you work. I tend to be a big hustler. So, there’s a lot more value-add that we want to make sure we bring to the table, even before investments. And then after the investment we can continue to bring that type of value to a company.

Are you investing outside of AI?

I’m investing in AI infrastructure, cybersecurity and AI-enabled apps. We are also at the verge of a big overhaul in terms of the application layer, companies that we’ve seen prior to AI — that is all getting disrupted.

We’re seeing AI scribes in healthcare intake solutions, for example. We’re seeing code-generation solutions in developer stacks. We are looking at every single vertical, as well as horizontal application. I’m very interested in how all of these verticals’ application layers will get a different type of automation.

What’s your take on the market overall right now?

I feel like I lived three lifetimes in my investing career — just over the past few years. We as a VC community and tech ecosystem learned a lot, obviously, just in terms of what’s happening. We’re seeing new ingredients in the market, and that is AI, that did not exist during COVID.

Think about the fact that this is not a structural change in the market driven by the economy. This is truly a new technology. I would bucket those waves as separate.

I’m very grateful to be investing at this time. What a time to be investing, because AI is truly game-changing as a technology.

Related Crunchbase query:

• Rounds Raised By Startups Using AI

Related reading:

• Dell Technologies Capital On The Next Generation Of AI — And The Data Fueling It
• From Web 2.0 To AI: How True Ventures Is Backing The Next Big Shift
• 7 Questions With Google Brain Founder Andrew Ng On How His Venture Studio Builds And Backs AI Startups
• Sierra Ventures On The 5 Layers Of AI Startup Investment 

Illustration: Dom Guzman

Methodology

This tracker includes layoffs conducted by U.S.-based companies or those with a strong U.S. presence and is updated at least bi-weekly. We’ve included both startups and publicly traded, tech-heavy companies. We’ve also included companies based elsewhere that have a sizable team in the United States, such as Klarna, even when it’s unclear how much of the U.S. workforce has been affected by layoffs.

Layoff and workforce figures are best estimates based on reporting. We source the layoffs from media reports, our own reporting, social media posts and layoffs.fyi, a crowdsourced database of tech layoffs.

We recently updated our layoffs tracker to reflect the most recent round of layoffs each company has conducted. This allows us to quickly and more accurately track layoff trends, which is why you might notice some changes in our most recent numbers.

If an employee headcount cannot be confirmed to our standards, we note it as “unclear.”

Venture funding has most definitely rebounded since the 2022 correction, but there’s a sharp divide between who’s getting funding and who’s not.

That was the overarching theme from our third-quarter market reports, which showed that global startup funding in Q3 totaled $97 billion, marking only the fourth quarter above $90 billion since Q3 2022.

Still, there are stark differences between the 2021 market peak and now, as contributing reporter Joanna Glasner noted in a couple of recent columns, here and here. Just as we saw four years ago, funding is frothy and often seems to be driven by investor FOMO. Some companies are even raising follow-on rounds at head-spinning speeds.

But the funding surge this time is also much, much more concentrated — namely in outsized rounds for AI companies.

With that, let’s take a look at the charts that illustrate the major private-market and startup funding themes as we head into the final quarter of 2025.

AI funding continues to drive venture growth

Nearly half — 46% — of startup funding globally in Q3 went to AI companies, Crunchbase data shows. Almost a third went to a single company: Anthropic, which raised $13 billion last quarter.

Even with an astonishing $45 billion going to artificial intelligence startups in Q3, it was only the third-highest quarter on record for AI funding, with Q4 2024 and Q1 2025 each clocking in higher.

Megarounds gobble up lion’s share

It shouldn’t come as too much of a surprise that AI has also skewed investment heavily toward megarounds, which we define as funding deals of $100 million or more.

The percentage of overall funding going into such deals hit a record high this year, with an astonishing 60% of global and 70% of U.S. venture capital going to $100 million-plus rounds, per Crunchbase data.

Even with several months left in the year, it also seems plausible that the total dollars going into such deals will match or top what we saw in 2021, which marked a peak for startup funding not scaled before or since.

The difference? Back then, startup dollars were widely distributed, going to a whole host of sectors — from food tech to health tech to robotics — and to early-stage, late-stage and in-between companies alike.

Contrast that with recent quarters, when the LLM giants and other large, established, AI-centric companies are getting the largest slice of venture dollars.

Seed deals slide further

As megarounds have increased, seed deals have declined.

The number of seed deals has shown a steady downward trend in recent quarters, Crunchbase data shows, even as total dollars invested at the stage has stayed relatively steady. That indicates that while seed deals are growing larger, they’re also harder to come by.

Early-stage funding has essentially flatlined, despite larger rounds to companies working on robotics, biotech, AI and other technologies.

The AI haves and have-nots

AI has enthralled investors for the past three years.

What are they less interested in? Old standbys like cybersecurity and biotech. Biotech investment as a share of overall funding recently hit a 20-year low. Crunchbase data shows that cybersecurity investment, while still relatively steady, also retreated somewhat in Q3 2025. That’s notable given that many cybersecurity companies are integrating AI into their offerings.

Still, other sectors that benefit heavily from AI-driven automation are seeing a surge in investment. Perhaps most notable is legal tech, which hit an all-time high last month on the back of large rounds for companies promising to automate much of the drudgery of the profession.

Among the other sectors buoyed by AI is human resources software (including AI-powered recruitment and hiring offerings).

Other data points of note

Other interesting points that emerged from our Q3 reports and recent coverage include:

• Unicorn creation in the third quarter swelled as 26 new billion-dollar startups trotted onto our Unicorn Board in September alone.
• Q3’s most-active investors were the serial backers in those AI megarounds. They included well-known names such as Insight Partners, General Catalyst, Accel, Andreessen Horowitz and Iconiq Capital.
• Funding for Asia-based startups rose sequentially in the third quarter, boosted by a handful of hardtech-focused megarounds.
• European startups raised $13.1 billion across more than 1,000 deals in Q3, flat quarter over quarter but up 22% year over year. Early-stage investment was particularly strong, and the region benefited from the excitement around Klarna’s long-awaited IPO.
• In Latin America, Brazil pushed Mexico out of the top spot to retake its crown as the region’s largest funding recipient.

Looking ahead

The increasing concentration of capital into a small cadre of large AI companies — not to mention the interconnectedness of those deals — begs some obvious questions. Are we in a bubble? And given that nearly half of venture capital in recent years has been tied up in AI, what happens to the startup ecosystem if or when it pops?

Related reading:

• Q3 Venture Funding Jumps 38% As More Massive Rounds Go To AI Giants And Exits Gain Steam
• North American Startup Funding Held High In Q3
• Europe’s Venture Scene Held Steady In Q3, Buoyed By Early-Stage Funding And Klarna IPO
• Asia Startup Investment Up In Q3
• Active Investors Kept Busy In An AI-Centric Quarter
• Brazil Back On Top In Q3 When It Comes To Venture Funding In Latin America

Illustration: Dom Guzman

By Yakov Filippenko

No founder plans for the day they get fired from their own company.

You plan for funding rounds, product launches and exits, but not for the boardroom moment when everyone raises their hand, and you realize your journey inside the company is over.

It happened to me. I called that board meeting. I set the vote. We had to choose who would stay, me or my co-founder. The vote didn’t go my way.

In movies, this is where the music swells and the credits roll. Steve Jobs after John Sculley. Travis Kalanick after Bill Gurley. In real life, there’s no cinematic pause. No final scene. Just the quiet realization that everything you built now belongs to someone else.

What follows isn’t drama, either. It’s disorientation. And like most founders, I had no idea how to handle it.

Don’t fill the silence too fast

When it ended, I filled my calendar with aimless meetings. Five or six a day. Not because they had any real purpose, but because it felt strange not to be doing business. For more than 10 years, I’d never had a day when I didn’t have to think about work. A startup teaches you to fix things fast.

When you’re out, though, there’s nothing left to fix. Only yourself. Getting pushed out isn’t like missing a quarterly target. It’s like losing the story you’ve been telling yourself for years.

The hardest part is that you don’t know who to blame.

Investors? They were doing their job. Yourself? Every decision made sense in context. So the frustration lands on the person closest to you. Your co-founder. It’s not about logic. I would say it is more of a defense mechanism. It’s how the mind tries to make sense of loss.

Learn to see the pattern

For months, I kept asking: What did we do wrong? It took me a couple of years to see the pattern.

Later, working inside a venture fund helped me see the truth. I saw the same story play out again and again. Founders repeating the same emotional arc, as follows:

• Expectation of an M&A deal;
• Long wait for the deal;
• The deal collapses;
• The startup stalls;
• Expectations diverge; and then
• Resentment between co-founders

Every time, the same sequence. And when the dream fades, blame fills the gap.

The pattern itself is that the anger toward a co-founder is often a projection of disappointment from a failed deal. If that energy isn’t processed consciously, it finds its own way out, usually as anger. You can’t really be mad at yourself; you did everything right. The other side acted in their own interest. So it lands on the person next to you, your co-founder and your team, and for them, it’s you.

And that’s where I have a bit of a claim toward investors because they often see this dynamic coming and could at least warn founders about it.

Once I recognized the pattern, I stopped seeing my story as a failure. It was part of a cycle almost every founder goes through, only most don’t talk about it.

Trade strategy for emotional tools

Traditional business tools didn’t help. OKRs, planning sessions, strategy off-sites, none of it worked on the inner collapse that comes when your identity and your company split apart.

This led me to begin studying Gestalt therapy. It gave me the language to understand how situations like this actually work, their cycles, causes and effects, and how to think about them with the right awareness and perspective. One part of building startups isn’t about pivots or fundraising. It’s realizing how much of yourself you’ve tied to the story you’re telling the world.

The point is to first get conscious of your anger, and then let it out.

Acceptance comes in stages

Acceptance doesn’t show up all at once. It arrives in pieces.

For me, the first piece came when I watched another founder go through the same breakdown and recognized every stage.

The second came when my first startup was acquired. Not at the valuation I’d dreamed of, but enough to accept that it continued without me. The third came with my current company, Intch, which is built from calm, not from fear.

I no longer measure success by control, but by clarity.

What I’d tell a founder in that room

Here’s what I’d share now with another entrepreneur who finds themselves in the same situation.

• You’re losing a story, not your worth. Give yourself space to grieve it.
• Don’t let anger choose a target. Name the pattern instead.
• Find mirrors. Other founders are walking through the same steps.
• Business tools have limits. Emotional tools matter here.
• Acceptance comes in stages. You’ll recognize them when they arrive.

Founders are trained to manage everything except their own psychology. But startups are way more than capital and code. They run on the emotional architecture of the people who build them. And when that structure breaks, rebuilding it is the most important startup you’ll ever work on.

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 Yakov Filippenko is a seasoned entrepreneur with more than 10 years of experience in IT and technologies, as well as scaling businesses internationally. As a product manager at Yandex, he led a team that grew the product’s user base from 500,000 to 1.2 million and secured its entry into the international market. Subsequently, he co-founded SailPlay, which he scaled to 45 countries and eventually exited, after it was acquired by Retail Rocket in 2018. In 2021, Filippenko launched Intch, an AI-powered platform connecting part-time professionals with flexible roles.

Illustration: Dom Guzman

Whatnot, a live shopping platform and marketplace, has closed a $225 million Series F round, more than doubling its valuation to $11.5 billion in less than 10 months.

DST Global and CapitalG co-led the financing, which brings the Los Angeles-based company’s total raised to about $968 million since its 2019 inception. Whatnot had raised $265 million in a Series E round at a nearly $5 billion valuation in January.

New investors Sequoia Capital and Alkeon Capital participated in the Series F, alongside returning backers Greycroft, Andreessen Horowitz, Avra and Bond. Other investors include Y Combinator, Lightspeed Venture Partners and Liquid 2 Ventures.

As part of the latest financing, Whatnot says it will initiate a tender offer where select current investors will buy up to $126 million worth of shares.

Funding to e-commerce startups globally so far this year totals $7.1 billion, per Crunchbase data. That compares to $11.3 billion raised by e-commerce startups globally in all of 2024. This year’s numbers are also down significantly from post-pandemic funding totals, which surged to $93 billion in 2021.

‘Retail’s new normal’

Live commerce is the combination of livestreaming and online shopping. Grant LaFontaine, co-founder and CEO of Whatnot, said in an announcement that his startup is “proving that live shopping is retail’s new normal.”

The company says more than $6 billion worth of items have been sold on its platform in 2025 so far, more than twice its total for all of 2024. Its app facilitates the buying and selling of collectibles like trading cards and toys through live video auctions. It also offers items such as clothing and sneakers. It competes with the likes of eBay, which currently does not offer a livestreaming option. It’s also a competitor to TikTok Shop.

“Whatnot brought the live shopping wave to the US, the UK, and Europe and has turned it into one of the fastest growing marketplaces of all time, Laela Sturdy, Whatnot board member and managing partner at CapitalG, Alphabet’s independent growth fund, said in a release.

The company plans to use its new funds to invest in its platform, roll out new features and “evolve” its policies. It is also accelerating its international expansion, adding to its current 900-person workforce by hiring across multiple departments.

Related query:

• Funding to E-Commerce Startups, 2025

Related Reading:

• TikTok Shop Rival Whatnot Bags $265M At $5B Valuation For Live Shopping Platform

Illustration: Dom Guzman

By Jeff Seibert

I’ve been building products and companies my entire career — Increo, Box, Crashlytics, Twitter and now, Digits — and I’ve had the privilege of speaking with some of the sharpest minds in venture and entrepreneurship along the way.

One recent conversation with a legendary investor really crystallized for me a set of truths about startups: what success really is, why some founders thrive while others burn out, and how to navigate the inevitable chaos of building something from nothing.

Here are some of the lessons I’ve internalized from years of building, observing and learning.

Success has no finish line

In the startup world, we talk a lot about IPOs, acquisitions and valuations. But those are milestones, not destinations.

The companies that endure don’t “win” and stop — they keep creating, adapting and pushing forward. They’re playing an infinite game, where the only goal is to remain in the game.

When you’re building something truly generative — driven by a purpose greater than yourself — there’s no point at which you can say “done.” If your company has a natural stopping point, you may be building the wrong thing.

You don’t choose the work — the work chooses you

The best founders I’ve met — and the best moments I’ve had as a founder — come from an almost irrational pull toward solving a specific problem I myself experienced.

You may want to start a company, but if you have to talk yourself into your idea, it probably won’t survive contact with reality. The founders who succeed are often the ones who can’t not work on their thing.

Starting a company shouldn’t be a career move — it should be the last possible option after every other path fails to scratch the itch.

The real killer: founder fatigue

Most companies don’t die because of one bad decision or one tough competitor. They die because the founders run out of energy.

Fatigue erodes vision, motivation and creativity. Protecting your own drive — keeping it clean and focused — may be the single most important survival skill you have.

That means staying close to the product, protecting time for customer work, and avoiding the slow drift into managing around problems instead of solving them.

Customer > competitor

It’s easy to get caught up in competitor moves, investor chatter or market gossip. But the most important question is always: Are we delivering joy to the customer?

If you’re losing focus, sign up for your own product as a brand-new user. Feel the friction. Fix it. Repeat.

At Digits, we run our own signup and core flows every week. It’s uncomfortable — it surfaces flaws we’d rather not see — but it keeps us anchored to the only metric that matters: customer delight.

Boards should ask questions, not give answers

Over the years, I’ve learned the most effective boards aren’t presentation theaters — they’re discussion rooms.

The best structure I’ve seen:

• No slides;
• A narrative pre-read sent in advance; and
• A deep dive into one essential question.

Good directors help you widen your perspective. They don’t hand you a to-do list. Rather, they help you see the problem in a way that makes the answer obvious.

Twitter: lessons from a phenomenon

When I think back to my time at Twitter, the most enduring lesson is that not all companies are built top-down. Some — like Twitter — are shaped more by their users than their executives.

Features like @mentions, hashtags and retweets didn’t come from a product roadmap — they came from the community.

That’s messy, but it’s also powerful. Sometimes your job isn’t to control the phenomenon, rather it’s to keep it healthy without smothering what made it magical in the first place.

Why now is a great time to start

If you’re building today, you have an advantage over the so-called “unicorn zombies” that raised massive rounds pre-AI and are now locked into defending old business models.

Fresh founders can design from scratch for the new reality; there’s no legacy to protect, no sacred cows to defend.

The macro environment? Irrelevant. The only timing that matters is when the problem calls you so strongly that not working on it feels impossible.

If there’s one takeaway from all of this, it’s that success is continuing. The real prize is the ability to keep playing, keep serving and keep creating.

If you’re standing at the edge, wondering if you should start — start. Take one step. See if it grows. And if it does, welcome to the infinite game.

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 Jeff Seibert is the founder and CEO of Digits, the world’s first AI-native accounting platform. He previously served as Twitter‘s head of consumer product and starred in the Emmy Award-winning Netflix documentary “The Social Dilemma.”

Illustration: Dom Guzman

While startup investment has been climbing lately, not all industries are partaking in the gains.

Cleantech is one of the spaces that’s been mostly left out. Overall funding to the space is down this year, despite some pockets of bullishness in areas like fusion and battery recycling.

The broad trend: Cleantech- and sustainability-related startup investment has been on a downward trajectory for several years now. And so far, 2025 is on track to be another down year.

On the bright side, however, there’s been some pickup in recent months, boosted by big rounds for companies in energy storage, fusion and other cleantech subsectors.

The numbers: Investors put an estimated $20 billion into seed- through growth-stage funding to companies in cleantech, EV and sustainability-related categories so far this year.

That puts 2025 funding on track to come in well below last year’s levels, which were already at a multiyear low.

Still, quarter by quarter, the pattern looks more encouraging. Investment hit a low point in Q1 of this year and recovered some in the subsequent two quarters. The current quarter is also off to a strong start.

Noteworthy recent rounds

The largest cleantech-related round of the year closed this month. Base Power, a provider of residential battery backup systems and electricity plans, raised $1 billion in Series C funding. The Austin, Texas-based company says its systems allow energy providers to more efficiently harness renewable power.

The second-largest round was Commonwealth Fusion Systems’ $863 million Series B2 financing. The Devens, Massachusetts-based company says it is moving closer to being the first in the world to commercialize fusion power.

For a bigger-picture view, below we put together a list of 10 of the year’s largest cleantech- and sustainability-related financings.

The broad takeaway: Startups innovating for an era of rising power consumption

Not to over-generalize, but if there was one big takeaway from recent cleantech and sustainability startup funding, it would be that founders and investors recognize that these are times of ever-escalating energy demand. They’re planning accordingly, looking to tap new sources of power, fusion in particular, as well as better utilize and scale existing clean energy sources.

Related Crunchbase query and list:

• Cleantech, EV & Sustainability-Related Funding, 2025 YTD
• Large 2025 Financings For Cleantech, EV And Sustainability Startups

Illustration: Dom Guzman

Correctly calling a market peak is a notoriously tricky endeavor.

Case in point: When tech stocks and startup funding hit their last cyclical peak four years ago, few knew it was the optimal time to cease new deals and cash in liquidatable holdings.

This time around, quite a few market watchers are wondering if the tech stock and AI boom has reached bubble territory. And, as we explored in Friday’s column, there are plenty of similarities between current conditions and the 2021 peak.

Even so, by other measures we’re also in starkly different territory. The current boom is far more concentrated in AI and a handful of hot companies. The exit environment is also much quieter. And of course, the macro conditions don’t resemble 2021, which had the combined economic effects of the COVID pandemic and historically low interest rates.

Below, we look at four of the top reasons why this time is different.

No. 1: Funding is largely going into AI, while other areas aren’t seeing a boom

Four years ago, funding to most venture-backed sectors was sharply on the rise. That’s not the case this time around. While AI megarounds accumulate, funding to startups in myriad other sectors continues to languish.

Biotech is on track to capture the smallest percentage of U.S. venture investment on record this year. Cleantech investment looks poised to hit a multiyear low. And consumer products startups also remain out of vogue, alongside quite a few other sectors that once attracted big venture checks.

The emergence of AI haves and non-AI have-nots means that if we do see a correction, it could be limited in scope. Sectors that haven’t seen a boom by definition won’t see a post-boom crash. (Though further declines are possible.)

No. 2: The IPO market is not on fire

The new offering market was on fire in 2020 and 2021, with traditional IPOs, direct listings and SPAC mergers all flooding exchanges with new ticker symbols to track.

In recent quarters, by contrast, the IPO market has been alive, but not especially lively. We’ve seen a few large offerings, with CoreWeave, Figma and Circle among the standouts.

But overall, numbers are way down.

In 2021, there were hundreds of U.S. seed or venture-backed companies that debuted on NYSE or Nasdaq, per Crunchbase data. This year, there have been less than 50.

Meanwhile, the most prominent unicorns of the AI era, like OpenAI and Anthropic, remain private companies with no buzz about an imminent IPO. As such, they don’t see the day-to-day fluctuations typical of public companies. Any drop in valuation, if it happens, could play out slowly and quietly.

No. 3: Funding is concentrated among fewer companies

That brings us to our next point: In addition to spreading their largesse across fewer sectors, startup investors are also backing fewer companies.

This year, the percentage of startup funding going to megarounds of $100 million or more reached an all-time high in the U.S. and came close to a record global level. A single deal, OpenAI’s $40 billion March financing, accounted for roughly a quarter of  U.S. megaround funding.

At the same time, fewer startup financings are getting done. This past quarter, for instance, reported deal count hit the lowest level in years, even as investment rose.

No. 4: ZIRP era is long gone

The last peak occurred amid an unusual financial backdrop, with economies beginning to emerge from the depths of the COVID pandemic and ultra-low interest rates contributing to investors shouldering more risk in pursuit of returns.

This time around, the macro environment is in a far different place, with “a “low fire, low hire” U.S. job market, AI disrupting or poised to disrupt a wide array of industries and occupations, a weaker dollar and a long list of other unusual drivers.

What both periods share in common, however, is the inexorable climb of big tech valuations, which brings us to our final thought.

Actually, maybe the similarities do exceed differences

While the argument that this time it’s different is a familiar one, the usual plot lines do tend to repeat themselves. Valuations overshoot, and they come down. And then the cycle repeats.

We may not have reached the top of the current cycle. But it’s certainly looking a lot closer to peak than trough.

Related Crunchbase query:

• Rounds Raised By Startups Using AI

Related reading:

• The Great ‘AI Bubble’ Debate
• The Last Market Boom Ended 4 Years Ago. Here’s How Current Conditions Look Similar
• Biotech Share Of US Funding Hits Lowest Point In Crunchbase History
• Cleantech On Track For Weak Funding Year
• A Record Share Of Startup Funding Is Going To $100M+ Rounds
• SoftBank And OpenAI Make History With Largest Startup Financing Ever

Illustration: Dom Guzman

By Vykintas Maknickas

The old cliché says startups are born in garages and dorm rooms. That’s still true, but there’s a newer path: founding a startup inside a scale-up.

When you do that, you get the speed of a seed-stage team with the leverage of an established company. Executives and investors should care because this model can unlock new product lines, revenue and talent retention without recreating the wheel.

That’s how we built Saily, a travel eSIM service launched from inside Nord Security (the company behind NordVPN). In 19 weeks, a seven-person team went from a blank page to a live product. A little over a year later, we had scaled to millions of users with plans offered in more than 200 destinations. We did not invent everything from scratch. We reused what worked and validated everything else fast.

Incubation lowers two risks most founders underestimate

Every new product faces two existential risks: market and execution.

Inside Nord, I’d helped launch at least half a dozen new products before Saily. The pattern was consistent: Great ideas die when they target the wrong market or underestimate execution. With Saily, timing and infrastructure lined up: eSIM demand was accelerating, pain points were clear, and we could tap Nord’s backend, payments, app teams and distribution.

That allowed us to move at startup speed without startup fragility.

‘Product organization fit’ beats a great idea

Founders obsess over product-market fit. Inside a scale-up, you also need what I call “product organization fit” or the overlap between a new product and what your company already does well.

When that overlap is high, you ship faster, hire smarter and avoid costly relearning. For Saily, the overlap was obvious: Security tech we knew (virtual location, web protection and ad-blocking), and app development know-how we could bring to travel connectivity.

Competition helped more than it hurt. “No competition” usually means “no demand.” We treated competitors as free market research, reading hiring signals, product moves and funding announcements to understand where the market was headed.

And we made security the product, not a feature. Travelers don’t want another app — they want reliable connectivity that isn’t risky on unknown networks. Building privacy and protection at the network layer means safety works phone-wide with no tinkering.

Autonomy inside structure

The hard part is not technical, but cultural. Large companies run on process. Startups run on autonomy. We set up Saily as a company within the company: A dedicated product and marketing team with decision speed, plus shared services (legal, finance and design) when needed. Think of it as an internal accelerator, where the platform handles overheads so the team can focus on products.

We kept one rhythm: ship, learn, repeat. Those 19 weeks weren’t about perfection, but about getting a usable product into the world and compounding feedback.

Experimentation only works if you measure what matters: speed, unit economics and retention. For example, independent third-party testing confirmed Saily’s network-level ad-blocking reduces data usage by 28.6% — real money saved for travelers. That is a signal you double down on. If a feature or tool adds complexity without value, cut it quickly.

What founders (and operators) can steal

• Derisk in two tracks: Validate market pull and execution feasibility before you scale spend. If the market isn’t growing and your organization doesn’t have overlap, think twice.
• Reuse before you reinvent: Borrow talent, systems and channels where you can. Every overlap removes weeks of risk.
• Measure what matters: Do a simple before/after on ship speed, customer acquisition cost and retention. If the needle doesn’t move, remove it.
• Build momentum in full sight: Share milestones and learning. It sharpens the team and attracts partners.

Saily is still early, and the market is just getting started, but the model matters as much as the product. Many future founders already work inside growth companies. Give them startup autonomy and scale-up leverage and remarkable things can happen — in months, not years.

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 Vykintas Maknickas is CEO of Saily, a global eSIM app from Nord Security. A former head of product strategy at NordVPN, where he helped launch a series of new product lines, Maknickas has turned Saily into a globally successful brand with millions of users and serving more than 200 destinations. An entrepreneur since age 15, Maknickas brings a hands-on, execution-driven approach to building secure, scalable consumer tech.

Illustration: Dom Guzman

Coinbase has been on a buying spree.

On Oct. 21, the publicly traded crypto exchange announced that it is acquiring early-stage investing platform Echo for $375 million in cash and equity.

Notably, the acquisition marked the eighth buy for the San Francisco-based company in 2025 so far, according to The Wall Street Journal. Of those eight deals, three involved undisclosed businesses.

Overall, since its 2012 inception, Coinbase has acquired dozens of companies, per Crunchbase data. Besides Echo, it announced purchases of the following startups in 2025:

• In January, it acquired Stryk, the Cyprus-based unit of BUX, as part of a European expansion. Stryk offers CFD trading services to European residents through an app. Financial terms were not disclosed
• Also in January, Coinbase picked up Spindl, a 3-year-old San Francisco-based startup that developed a blockchain-based attribution system to help businesses accelerate user growth.
• In May, it acquired Deribit, a 10-year-old cryptocurrency derivatives exchange offering options, futures and spot trading for digital assets based in the Netherlands.
• Then in July, Coinbase acquired Liquifi, a 4-year-old San Francisco-based startup that helps crypto companies automate their token vesting and lockups, and manage their token cap table. Liquifi was a self-described “Carta for crypto.”
• Now it has announced plans to buy Echo, an onchain digital platform that helps communities invest together and aims to give founders more options for their cap table.

Coinbase’s buying sprees seem to come in spurts, according to the data.

Crypto’s crash and recovery

For example, in 2018, it acquired eight known companies. And then in 2021, it picked up seven known companies. But most years, it acquired only one or two companies.

Interestingly, 2018 was defined by what has been described as the “Great Crypto Crash,” or a massive market sell-off after the boom that took place in 2017. Things had rebounded by 2021, which saw a bull market for crypto and the rise of NFTs and DeFi. That November, Bitcoin hit an all-time high of $68,000.

After a bumpy few years, which saw the arrests of FTX founder Sam Bankman-Fried and Binance CEO and founder Changpeng Zhao, Bitcoin has rebounded, surging to an all-time high in 2025. Prices reached $113,156.57 on Oct. 15.

In announcing its plan to acquire Echo, Coinbase said the two companies shared a similar mission of “democratizing early-stage investing, so that more people can support the next generation of breakthrough companies.”

The buy complemented its earlier acquisition of Liquifi, Coinbase said, noting that: “While Liquifi strengthened our ability to support builders at the start of their journey, Echo extends that support into fundraising.”

The largest of its acquisitions in 2025 so far, though, was its $2.9 billion buy of Deribit.

Meanwhile, Coinbase’s market cap as of Oct. 23 hovered just under $83 billion, while its stock is up over 25% year to date.

Related Crunchbase list:

• Coinbase Acquisitions 2012 To Date

Related Reading:

• Shares of Blockchain Lender Figure Surge 24% Higher In First Day On Nasdaq
• Circle Shares Soar 168% In First Day On NYSE, Potentially Unlocking IPO Market
• Why More Startups Are Buying Other Startups In 2025

Illustration: Dom Guzman

Want to keep track of the largest startup funding deals in 2025 with our curated list of $100 million-plus venture deals to U.S.-based companies? Check out The Crunchbase Megadeals Board.

This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding rounds here.

This was another active week for large startup financings. AI data center developer Crusoe Energy Systems led with $1.38 billion in fresh financing, and several other megarounds were AI-focused startups. Other standouts hailed from a diverse array of sectors, including battery recycling, biotech and even fire suppression.

1. Crusoe Energy Systems, $1.38B, AI data centers: Crusoe Energy Systems, a developer of AI data centers and infrastructure, raised $1.38 billion in a financing led by Valor Equity Partners and Mubadala Capital. The deal sets a $10 billion+ valuation for the Denver-based company.

2. Avride, $375M, autonomous vehicles: Avride, a developer of technology to power autonomous vehicles and delivery robots, announced that it secured commitments of up to $375 million backed by Uber and Nebius Group. The 8-year-old, Austin, Texas-based company said it plans to launch its first robotaxi service on Uber’s platform in Dallas this year.

3. Redwood Materials, $350M, battery recycling: Battery recycling company Redwood Materials closed a $350 million Series E round led by Eclipse Ventures with participation from new investors including Nvidia’s NVentures. Founded in 2017, the Carson City, Nevada-based company has raised over $2 billion in known equity funding to date.

4. Uniphore, $260M, agentic AI: Uniphore, developer of an AI platform for businesses to deploy agentic AI, closed on $260 million in a Series F round that included backing from Nvidia, AMD, Snowflake Ventures and Databricks Ventures. The round sets a $2.5 billion valuation for the Palo Alto, California-based company.

5. Sesame, $250M, voice AI and smart glasses: San Francisco-based Sesame, a developer of conversational AI technology and smart glasses, picked up $250 million in a Series B round led by Sequoia Capital. The startup is headed by former Oculus CEO and co-founder Brendan Iribe.

6. OpenEvidence, $200M, AI for medicine: OpenEvidence, developer of an AI tool for medical professionals that has been nicknamed the “ChatGPT for doctors” reportedly raised $200 million in a GV-led round at a $6 billion valuation. Three months earlier, OpenEvidence pulled in $210 million at a $3.5 billion valuation.

7. Electra Therapeutics, $183M, biotech: Electra Therapeutics, a developer of therapies against novel targets for diseases in immunology and cancer, secured $183 million in a Series C round. Nextech Invest and EQT Life Sciences led the financing for the South San Francisco, California-based company.

8. LangChain, $125M, AI agents: LangChain, developer of a platform for engineering AI agents, picked up $125 million in fresh funding at a $1.25 billion valuation. IVP led the financing for the 3-year-old, San Francisco-based company.

9. ShopMy, $70M, brand marketing: New York-based ShopMy, a platform that connects brands and influencers, landed $70 million in a funding round led by Avenir. The financing sets a $1.5 billion valuation for the 5-year-old company.

10. Seneca, $60M, fire suppression: Seneca, a startup developing a fire suppression system that includes autonomous drones that help spot and put out fires, launched publicly with $60 million in initial funding. Caffeinated Capital and Convective Capital led the financing for the San Francisco-based company.

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of Oct. 18-24. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

Illustration: Dom Guzman

Nearly four years ago, the market hit a cyclical peak under conditions that in many ways look quite similar to what we’re seeing today.

Sky-high public tech valuations. Booming startup investment. Sharply rising valuations. And, a few cracks emerging on the new offering front.

Sure, there are quite a few differences in the investment environment, which we’ll explore in a follow-on piece. For this first installment, however, we are focusing on the commonalities, with an eye to the four highlighted above.

No. 1: Sky-high public tech valuations

First, both then and now, tech stocks hit unprecedented highs.

In mid-November 2021, the tech-heavy Nasdaq Composite index hit an all-time peak above 16,000. Gains stemmed largely from sharply rising tech share prices.

Today, the Nasdaq is hovering not far below a new all-time high of over 23,000. The five most valuable tech companies have a collective market cap of more than $16 trillion. Other hot companies, like AMD, Palantir Technologies and Broadcom have soared to record heights this year.

While private startups don’t see day-to-day valuation gyrations like publicly traded companies, their investors do take cues from public markets. When public-market bullishness subsides, private up rounds tend to diminish as well.

No. 2: Booming startup investment

In late 2021, just like today, venture investment was going strong.

Last time, admittedly, it was much stronger. Global startup funding shattered all records in 2021, with more than $640 billion invested. That was nearly double year-earlier levels. Funding surged to a broad swathe of startup sectors, with fintech in particular leading the gains.

For the first three quarters of this year, by contrast, global investment totaled a more modest $303 billion. However, that’s still on track for the highest tally in years. The core driver is, of course, voracious investor appetite for AI leaders, evidenced by OpenAI’s record-setting $40 billion financing in March.

The pace of unicorn creation is also picking up, which brings us to our next similarity.

No. 3: Up rounds and sharply rising valuations

At the last market peak, valuations for hot startups soared, driven in large part by heated competition among startup investors to get into pre-IPO rounds.

This time around, we’re also seeing sought-after startups raising follow-on rounds in quick succession, commonly at sharply escalated valuations. Per Crunchbase data, dozens of companies have scaled from Series A to Series C within just a couple of years, including several that took less than 12 months.

We’re also seeing prominent unicorns raising follow-on rounds at a rapid pace this year. Standouts include generative AI giants as well as hot startups in vertical AI, cybersecurity and defense tech.

No. 4: A few cracks emerging

During the 2021 market peak, even when the overall investment climate was buzzier than ever, we did see some worrisome developments and areas of declining valuations.

For that period, one of the earlier indicators was share-price deterioration for many of the initial companies to go public via SPAC. By late 2021, it had become clear that there were numerous “truly terrible performers” among the cohort, including well-known names such as WeWork, Metromile and Buzzfeed.

This time around, the new offerings market hasn’t been quite so active. But among those that did go public in recent months, performance has been decidedly mixed. Shares of Figma, one of the hottest IPOs in some time, are down more than 60% from the peak.

Online banking provider Chime and stablecoin platform Circle have shown similar declines.

At this point, these are still generously valued companies by many metrics. But it’s also worth noting the share price direction in recent months has been downward, not upward.

Next: Watch for more cracks

Looking ahead, one of the more reliable techniques to determine whether we are approaching peak or already past is to look for more cracks in the investment picture. Are GenAI hotshots struggling to secure financing at desired valuations? Is the IPO pipeline still sluggish? Are public tech stocks no longer cresting ever-higher heights?

Cracks can take some time to emerge, but inevitably, they do.

Related reading:

• Global Venture Funding And Unicorn Creation In 2021 Shattered All Records 
• Q1 Global Startup Funding Posts Strongest Quarter Since Q2 2022 With A Third Going To Massive OpenAI Deal  
• Highest Count Of New Unicorns Join Crunchbase Board In Over 3 Years As Exits Also Gain Steam
• These Are The Speediest Companies To Go From Series A To Series C
• Truly Terrible Performers Multiply Among Startups Taking SPAC Route To Market

Illustration: Dom Guzman

By Alexander Lis

AI startups are raising capital at record speed. According to Crunchbase data, AI-related companies have already raised $118 billion globally in 2025. And, so far, traction looks impressive. AI startups are posting stellar revenue growth, and even the $100 million ARR milestone is often achieved.

While this growth is breathtaking, some analysts are beginning to question its sustainability. They warn that AI spending may soon reach a peak and that unprofitable tech companies could be hit hardest when the cycle turns. If that happens, many investors in AI will find themselves in a difficult position.

Predicting a bubble is rarely productive, but preparing for volatility is. It would be wise for both founders and investors to ensure that portfolio companies have enough resilience to withstand a potential market shock.

The key lies in assessing the durability of ARR. In a major downturn, the “growth game” quickly becomes a survival game. History suggests that while a few companies may continue to grow more slowly, the majority will struggle or disappear.

The question, then, is how to tell the difference between sustainable and hype-driven ARR.

What distinguishes durable ARR from hype?

Several factors set true, sustainable revenue growth apart from hype.

The first is customer commitment. Sustainable revenue comes from multiyear contracts, repeat renewal cycles and budgeted spend within core IT or operating lines. When revenue depends on pilots, proofs of concept or amorphous “innovation” budgets, it can vanish when corporate priorities shift. A company that touts these short trials as ARR is really reporting momentum, not recurring income.

This is what investor Jamin Ball has called experimental recurring revenue.

Traditional software firms can thrive with monthly churn in the low single digits — think 5% to 7%. But many AI companies are seeing double that. This means they have to sprint just to stand still, constantly replacing users who move on to the next shiny tool.

Another differentiator? Integration and workflow depth. Durable ARR is embedded into the customer’s core workflows, data pipelines or multiple teams. Ripping it out would be costly and disruptive. Hype ARR, by contrast, lives on the surface — lightweight integrations, fast deployments and limited stakeholders. Without unique intellectual property or deep workflow integration, such products can be replaced with minimal friction.

And finally, real growth is defined by clear value-add. True ARR is backed by measurable ROI, well-defined outcomes and long-term customer roadmaps.

In contrast, hype ARR is driven by urgency (we need to show our shareholders our AI deployment ASAP), or undefined ROI. In those cases, customers don’t even know how to define success. They are testing, not committing.

Beyond ARR

It is important to put ARR traction in context. Investors and founders should focus on a broader set of indicators — conversion from pilots to long-term contracts, contract length and expansion, net revenue retention, and gross margin trajectory. These metrics reveal if growth is sustainable.

It would also be helpful to assess the product’s real impact: efficiency uplift (more code, content, or customer conversations per employee-hour), accuracy improvement (e.g. for detecting bad actors), and higher conversion rates, among others. These metrics should exceed client expectations and outperform alternative tools. That’s what signals genuine value creation and a higher chance for experimental revenue to turn into durable ARR.

After all, AI may be changing how fast companies can form and grow, but it hasn’t suspended the basic laws of business.

For founders, the message is simple: Celebrate ARR if you so wish, but pair it with proof of retention, profitability and defensibility. For investors, resist the urge to chase every eye-popping run rate. The real competitive edge in this next phase of AI is stability, not spectacle.

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Alexander Lis is the chief investment officer at Social Discovery Ventures. With 10-plus years of experience across public markets, VC, PE and real estate, he has managed a public markets portfolio that outperformed benchmarks, led early investments in Sumsub, Teachmint and Byrd, and achieved 20%-plus IRR by investing in distressed real estate across the U.S.

Illustration: Dom Guzman

Editor’s note: This article is part of an ongoing series in which Crunchbase News interviews active investors in artificial intelligence. Read previous interviews with Foundation Capital, GV (formerly Google Ventures), Felicis, Battery Ventures, Bain Capital Ventures, Menlo Ventures, Scale Venture Partners, Costanoa, Citi Ventures, Sierra Ventures, Andrew Ng of AI Fund, and True Ventures, as well as highlights from more interviews done in 2023.

Fueled by AI, both Dell and its investment arm are on a hot streak this year.

The PC maker has seen demand for its server products surge with $20 billion in AI server shipments projected for fiscal 2026. At the same time, its investment arm, Dell Technologies Capital (DTC), has notched five exits — an IPO and four acquisitions — since June, an especially notable track record in a venture industry that has been challenged in recent years by a liquidity crunch.

On the heels of that success, we recently spoke with Dell Technologies Capital managing director Daniel Docter and partner Elana Lian.

DTC was founded more than a decade ago and operates as a full-stack investor, backing everything from silicon to applications.

“One big part of our network is the Dell relationship, which is the leader in GPU servers,” said Docter. As a result, Dell is connected to all the major players in the AI space, he said.

One of its earliest AI investments was during the machine-learning era in 2014 in a company called Moogsoft. Dell went on to acquire the alert remediation company in 2023.

DTC’s investment thesis was that the advent of machine learning was going to disrupt the tech industry. At that time, data had expanded to such a degree that new tools were required by the market to analyze data and find patterns, which informed the firm’s early investments in AI.

The investment team at DTC is largely comprised of  technical people, often “double E” degree engineers.

Docter has an electrical engineering background, worked at Hughes Research Labs, now HRL Laboratories, and transitioned from engineering to business development. He joined the venture industry 25 years ago and spent more than a decade at Intel. He joined DTC in 2016 through Dell’s EMC acquisition.

Lian worked in semiconductors for a decade, joined Intel Capital in 2010, and then joined Dell Technologies Capital in 2024.

Data evolution

Docter believes we are in the fifth generation of AI, which becomes more powerful with every iteration.

“We’re seeing that AI is almost a data problem,” said Lian. “For AI to get better and better, there’s an uncapped ceiling where there’s high-quality data coming in.”

The team is meeting startups focused on training, inference, reasoning and continuous learning along with safety requirements. Data is core to these advancements.

Even the definition of data is changing. “It used to be a word, then it was a context, then it was a task or a rationale or a path. Then it’s reasoning,” said Docter. “Who knows what’s next?”

As AI improves, there is demand for frontier data and for specialized data in fields such as philosophy, physics, chemistry and business. Humans are in the loop as these capabilities expand, said Docter, which has informed some of the firm’s investments.

On deal flow

DTC is a financial investor, assessing a potential company on whether it is a good investment, rather than backing businesses based on Dell’s strategic goals.

Startup revenue is exceeding what was previously possible, Docter said: “I’ve been doing this for 25 years. I’ve never seen companies that have this type of revenue growth.”

The best deals are always hotly contested, he noted.

The question to ask when it comes to revenue, Docter said, is: “Is that an innovation CTO office budget? Or is that a VP of engineering budget?”

When assessing a potential portfolio investment the team asks: “Is revenue durable? Is there value in using this?”

The pace of investment also seems unprecedented. “We’ll meet with a company on a Tuesday for the first time and sometimes by Thursday, they have a term sheet that they’ve already signed,” he said.

The firm does not have a dedicated fund size, which is an advantage as it can be flexible in the size of the check as well as the stage to make a commitment and how it invests over time.

DTC has invested $1.8 billion to date across 165 companies. It likes to invest early, at seed or Series A, with check sizes running from $2 million to $12 million, and leads or co-leads 80% of new deals. The firm makes around 15 to 16 new investments per year.

Once DTC has invested, it looks at how the firm can help portfolio companies sell to potential customers across Dell’s deal partner network.

This year, DTC has posted five exits, including Netskope’s IPO and four acquisitions: Rivos by Meta, SingleStore by Vector Capital, TheLoops by Industrial & Financial Systems and Regrello by Salesforce 1.

Notable AI investments

DTC is investing a little more actively than it has in the past, but remains disciplined, Docter said. The investment team is focused on complex enterprise use cases and challenges, following the Warren Buffett rule, which is to invest in what you know.

The firm invests at the silicon level because you “can be incredibly disruptive to the ecosystem,” said Docter.

The DTC portfolio companies we discussed include the following in areas ranging from silicon to applications.

Infrastructure and hardware layer:

• AI chipmaker Rivos, which Meta plans to acquire for an undisclosed amount. (The deal is pending regulatory approval.)
• SiMa.ai, which makes a chip for embedded edge use cases including in automobile, drone and robot technologies.
• Runpod, an AI developer software layer with on-demand access to GPUs. It allows developers to play with AI and then scale it to production. The service has 500,000 developers, including 30,000 paying monthly, said Docter.
• SuperAnnotate, a data annotation platform for enterprises with humans in the loop to build accurate data pipelines. Its customers include Databricks and the women’s health app Flo Health.

Applications:

• Maven AGI provides customer support for complex and high-compliance enterprise use cases, a potentially massive market. Lian projects customer experience overall will be a trillion-dollar market.
• Series Entertainment, a GenAI platform for game development that aims to reduce deployment timelines from eight months to two weeks.

What’s next?

A major area of interest for Lian is advancements in voice AI, the day-to-day human interaction with a machine.

It’s hard to imagine that the transformer architecture is the last and final architecture, said Docter. The firm has made investments in companies creating different architectures in Cartesia, a leader in state-space model, which has a longer context window building a new reasoning model with a different architecture, initially focused on voice AI. DTC has also invested in Israeli-based AA-I Technologies, which is working on a new type of reasoning model architecture.

“Right now, the opportunity of AI is this big, but this ball keeps on exploding,” said Lian. “The contact area is getting bigger and bigger. And that’s the same for the data.”

Related Crunchbase list:

• Dell Technologies Capital AI Portfolio

Illustration: Dom Guzman