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

In a competitive hiring environment, the ability to find exceptional talent that isn鈥檛 necessarily knocking down your door is hugely desired and not always easy to attain. That鈥檚 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, , has secured $51 million in equity and debt funding, the company tells 附近上门 News exclusively.

The raise includes a $36 million Series C led by (Silver Lake Waterman) with participation from , 听补苍诲 , as well as $15 million in growth financing from . The financing brings Findem鈥檚 total funding since its 2019 inception to $105 million, with $90 million of that being equity, per the company.

Redwood City, California-based Findem鈥檚 mission is simple, even if its methods are not. It aims to transform how businesses 鈥渋dentify, attract and engage top talent.鈥�

The startup uses what it calls (out of a dataset developed out of 1.6 trillion data points) that it combines with AI to automate 鈥渒ey parts of the talent lifecycle.鈥� And those parts include building 鈥渢op-of-funnel鈥� pipelines of interested candidates, executive search and analyzing workforce and labor markets.

In an interview with 附近上门 News, co-founder and CEO said that Findem鈥檚 user base surged by 鈥渁bout 100x鈥� 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 , , , 听补苍诲 , 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 附近上门 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鈥檚 platform in action provides better insight into just how it helps companies zero in on the specific talent for which they鈥檙e 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 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鈥檚 software will allow you to filter for all those desired attributes.

The startup says it鈥檚 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 鈥渃ontinuously enhanced鈥� 3D dataset is 鈥渆xponentially larger and more factual鈥� 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 鈥渆nriched鈥� profiles, for every candidate it helps surface. The goal of the profiles is to provide 鈥渁 detailed and factual view鈥� of an individual鈥檚鈥減rofessional journey and impact,鈥�

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).听

Those sources include , GitHub, , , personal websites, the , 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.听

It also pulls applicant profile information from applicant tracking systems such as , , , , and , among others.

This comprehensive data pull is what helps set Findem apart, in Kolam鈥檚 view. Some other hiring tools rely on one-dimensional data from resumes or LinkedIn profiles, which, he argues, 鈥済ive only a snapshot of someone鈥檚 career 鈥� without the context that reveals true potential.鈥� Kolam contends that it takes 鈥渆xtensive manual effort鈥� to verify and interpret the data.

鈥淛ust 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,鈥� Kolam maintains.

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

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

, managing partner at SLW, told 附近上门 News via email that his firm first got to know Kolam before Findem raised its Series B and then 鈥渢racked the company鈥檚 trajectory for some time.鈥�

鈥樷€橶hat drew us to Findem wasn鈥檛 just the technology, it was the traction,鈥� he said. “The team has achieved strong commercial momentum while tackling one of the most persistent challenges in HR 鈥� connecting data, insight and human potential in a way that actually drives business outcomes.鈥�

But the technology didn鈥檛 hurt.

In O鈥橬eill鈥檚 view, Findem鈥檚 main differentiator is its 鈥渄ata advantage 鈥� in a market where most companies are simply wrapping LLMs.鈥�

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

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