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

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.”

Related Crunchbase lists and queries:

• Global Funding To HR Software Companies In 2025
• Recently Funded Startups At The Intersection Of AI And Recruiting
• Recently Funded Freelance- And Gig-Related Startups
• Funding Tied To Enhancing Worker Productivity With AI/Emerging Tech

Related reading:

• Funding To HR Software Startups Rises As M&A Activity Heats Up 
• ​​Job-Related Startup Funding Points To More AI Screening And More ‘Gigification’ Of Work
• Exclusive: With OpenAI and Shopify As Customers, Ashby Raises $50M Series D For AI-Powered Talent Platform

Illustration: Dom Guzman