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The State Of Startups In 7 Charts: These Sectors And Stages Are Down As AI Megarounds Dominate In 2025

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:

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?

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Illustration: Dom Guzman

Exclusive: Findem Lands $36M Series C To Supercharge AI-Powered Hiring 

In a competitive hiring environment, the ability to find exceptional talent that isn’t necessarily knocking down your door is hugely desired and not always easy to attain. That’s why so many companies these days are turning to AI-powered talent acquisition and management startups to help them mine for exceptional candidates.

One such startup, Findem, has secured $51 million in equity and debt funding, the company tells Crunchbase News exclusively.

The raise includes a $36 million Series C led by SLW (Silver Lake Waterman) with participation from Wing Venture Capital, Harmony Capital and Four Rivers Group, as well as $15 million in growth financing from JP Morgan. The financing brings Findem’s total funding since its 2019 inception to $105 million, with $90 million of that being equity, per the company.

Redwood City, California-based Findem’s mission is simple, even if its methods are not. It aims to transform how businesses “identify, attract and engage top talent.”

The startup uses what it calls 3D talent data (out of a dataset developed out of 1.6 trillion data points) that it combines with AI to automate “key parts of the talent lifecycle.” And those parts include building “top-of-funnel” pipelines of interested candidates, executive search and analyzing workforce and labor markets.

In an interview with Crunchbase News, co-founder and CEO Hari Kolam said that Findem’s user base surged by “about 100x” in the last 12 months and that the company is experiencing 3x year-over-year growth. Its enterprise customer base increased by 3x over the last year.

It has a user base of more than 12,000 customers, including from Adobe, Box, Medallia, Nutanix and RingCentral, Kolam said.

Currently, Findem operates under a SaaS business model, charging per seat. As it expands its agentic abilities, the company plans to add an outcome-based model as well, according to Kolam. It is not yet profitable.

Findem is just one of more than a dozen startups at the intersection of AI and recruitment globally that have raised venture capital in 2025. As of early September, global startup investment for startups in the HR, recruitment and employment categories totaled around $2.3 billion, per Crunchbase data. That puts funding on track for a year-over-year gain, even as investment remains at a fraction of the levels hit during the market peak, as charted below.

 

How it works

Watching Findem’s platform in action provides better insight into just how it helps companies zero in on the specific talent for which they’re searching.

Say a startup wants to hire a software engineer who has worked at a company from its early days until it raised a Series C funding round. But it also wants that engineer to have a GitHub profile that it can view. Or, say a company wants to hire competitive coders who have seen a successful exit, or a CFOs who drove a company from a negative operating margin to a positive one.

Findem’s software will allow you to filter for all those desired attributes.

The startup says it’s able to help companies recruit so specifically because its 3D data combines people and company data over time into a format suitable for AI analysis. It claims that the “continuously enhanced” 3D dataset is “exponentially larger and more factual” than traditional sources of candidate data, making it a powerful tool for deep insights and automated workflows.

Using the combination of the data and AI, Findem creates 3D profiles, also dubbed “enriched” profiles, for every candidate it helps surface. The goal of the profiles is to provide “a detailed and factual view” of an individual’s “professional journey and impact,”

So just where does all this data come from? Findem says it continuously leverages a language model to generate that 3D data from more than 100,000 sources that are chronologically gathered (from earliest to latest). 

Those sources include LinkedIn, GitHub, Doximity, WordPress, personal websites, the U.S. Census Bureau, company funding announcements and IPO details, business models, more than 300 million patents and publications, over 5 million open datasets and ML projects, and over 200 million open source code repositories. 

It also pulls applicant profile information from applicant tracking systems such as Workday, BambooHR, Bullhorn, Greenhouse, Jobvite and Lever, among others.

This comprehensive data pull is what helps set Findem apart, in Kolam’s view. Some other hiring tools rely on one-dimensional data from resumes or LinkedIn profiles, which, he argues, “give only a snapshot of someone’s career … without the context that reveals true potential.” Kolam contends that it takes “extensive manual effort” to verify and interpret the data.

“Just looking at a resume on paper really doesn’t come close to telling the whole story of how really qualified a candidate could be, or if they can really fit the criteria that a particular employer is looking for,” Kolam maintains.

Findem is primarily focused on North American customers who have users across the globe. It’s also expanding into Europe. The company has a second headquarters in Bangalore, India.

Kolam declined to reveal Findem’s valuation, saying only that it was “a significant up round and more than 2x” compared to its valuation when it raised a $17 million-plus Series B extension in December 2023.

Shawn O’Neill, managing partner at SLW, told Crunchbase News via email that his firm first got to know Kolam before Findem raised its Series B and then “tracked the company’s trajectory for some time.”

‘’What drew us to Findem wasn’t just the technology, it was the traction,” he said. “The team has achieved strong commercial momentum while tackling one of the most persistent challenges in HR — connecting data, insight and human potential in a way that actually drives business outcomes.”

But the technology didn’t hurt.

In O’Neill’s view, Findem’s main differentiator is its “data advantage … in a market where most companies are simply wrapping LLMs.”

“The depth and breadth of their 3D profiles and web-scale dataset are unlike anything else in the market,” he said. “The UX is excellent, but the magic is really in how the platform leverages that data — it makes finding and understanding people effortless. We use it ourselves and see the power firsthand.”

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Illustration: Dom Guzman

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