Spott - Spott is the AI-native ATS & CRM for recruiting firms
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Spott is the AI-native ATS/CRM built for staffing and recruiting firms to manage candidates, automate workflows, and close placements faster.
AI at the core, not bolted on. Match candidates by context, not keywords. Auto-enrich profiles. Generate candidate presentations in seconds.
One platform replacing your entire stack: outreach, note-taking, analytics, scheduling, and more. Connected to mail, WhatsApp, LinkedIn, calendar, and VOIP.
Backed by Y Combinator (W25).
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Hey Product Hunt! Kevin here from the Spott team.
Spott started with three friends: Manu, Lander, and Samuel. They met eight years ago studying business engineering at KU Leuven, all ended up in management consulting (McKinsey, BCG, and Bain), and all independently rotated through projects at staffing and recruiting agencies across Europe, the UK, and the Middle East.
They each saw the same thing: recruiters spending half their day logging activities instead of making placements. ATS systems that stored data but never did anything with it. When they started comparing notes, they realized they'd all arrived at the same frustration and the same idea.
Their first instinct was the sensible one: add AI on top of existing platforms like Bullhorn and Salesforce. It didn't work. You can bolt a chatbot onto a relational database, but you can't make it truly understand context. So they made the harder choice. Quit their jobs. Start from zero.
They applied to Y Combinator with a candidate report writer. By demo day, they'd pivoted to a full AI-native ATS built on a vectorized database that understands the meaning of everything stored in it, not just keywords. 60 investor meetings later, they raised $3.2M led by Base10 Partners.
Today Spott is used by recruiting firms across every continent. We're building toward a platform that handles the bulk of recruitment workflows autonomously, so recruiters can focus on what actually requires human judgment: relationships, negotiation, and knowing whether someone will thrive in a role.
Would love your feedback!
Interesting take on rebuilding the ATS around semantic search instead of a relational model. How does that change the way recruiters actually navigate candidate data day to day?
@artem_kosilov Everything feeds into one system: meeting notes, phone calls (VOIP), LinkedIn, WhatsApp, inbound applications, LinkedIn job slots, your vacancy portal, or API. All under one roof.
When a recruiter describes what they need, the system searches across all of that, not just CVs. Inbound applications get auto-ranked the same way. Recruiters stop building Boolean filters and start describing what they're looking for.
Important note: it's not a black box. Spott shows why each candidate was matched, so the recruiter understands the reasoning. And at the end of the day, it's still the recruiter who makes the final call. The AI surfaces and ranks, the human decides.
@kevin_vandeputte, the founding story is the homepage. Three McKinsey/BCG/Bain consultants who all independently hit the same wall. That's not a feature. That's a category origin story.
Right now the homepage opens with "Recruiting, rebuilt for today and tomorrow." Every ATS on the internet says a version of that.
But your PH comment tells the real story. Three consultants. Same frustration. Quit their jobs. Built from zero because bolting AI onto existing platforms was never going to work.
That story is sitting in a comment section instead of your hero. And that's exactly where conversions are being lost.
Congrats on the launch.
@taimur_haider1 Thanks for the kind words. You're not wrong. The founding story resonates more than a tagline ever will. We're working on it. 💪
@kevin_vandeputte That's the spirit. And when you do tell it, don't polish it too much. The raw version is the powerful one. Three consultants. Same frustration. Quit their jobs. Built from zero.
That sentence doesn't need a copywriter. It just needs a homepage.
ATS tools I worked with were useless for career switchers — someone moving from sales to customer success would never show up in a keyword search. Context-based matching sounds like it could fix that. How well does Spott handle non-linear career paths where the relevant experience is not in the job title?
@klara_minarikova This is exactly one of the problems semantic matching solves. A Sales Manager moving to Customer Success would never surface in a keyword ATS. In Spott, the system understands that managing client relationships and driving renewals are shared competencies. That candidate shows up automatically.
It goes beyond CVs too. If a recruiter spoke with that candidate six months ago and noted "looking to transition into CS, strong account management background," that context factors into future matches. We capture it from every channel: calls, meetings, LinkedIn, WhatsApp, notes...
Career switchers are actually some of the richest profiles in a semantic system. More diverse experience means more data points for the AI to work with.
The attention to detail in every nook and cranny of the UI is simply astounding.
The WhatsApp and LinkedIn integrations are interesting too, since that's where most recruiting conversations actually happen. Curious about something - when a recruiter logs a quick voice note or informal chat summary, does Spott's AI pick up on those soft signals too, or does it mainly work with structured profile data?