FindThem

GMAC Member

GMA Community

"Hey Product Hunt! 👋 I'm Kuda, the maker of FindThem. The problem: Every founder raising capital, every sales rep building a pipeline, and every recruiter sourcing candidates does the same thing, they spend hours scrolling through LinkedIn, guessing at search filters, and copy-pasting profiles into spreadsheets. LinkedIn Sales Navigator costs $100+/mo and still makes you do the manual work. To solve it I built: FindThem lets you describe who you're looking for in plain English like "angel investors in healthtech, based in EU, invested pre-seed in last 12 months" and our AI searches across 1B+ LinkedIn profiles, cross-referenced with data from the entire web. You get back verified emails, LinkedIn URLs, enriched company data, and a relevance score explaining why each person matches. How it works: Search → describe your ideal person in natural language Enrich → every result comes with verified contact data Export → CSV, plug into your CRM What makes us different: No LinkedIn Premium or Sales Navigator needed Pay per profile found — no subscriptions, no per-seat pricing AI relevance scoring explains why each match fits your criteria We're a small team and built this because we were tired of spending 10+ hours building a single prospect list manually. Now it takes minutes. Coming soon: AI-drafted personalized outreach for every person on your list. Would love to hear - what's your biggest frustration when trying to find the right people to reach out to? 💬 Try it free at findthem.pro -> no credit card needed."

GMAC Member

GMA Community

"does natural language search actually handle descriptions like 'fintech operator who's exited once and is now investing in b2b saas' differently from keyword search, or is the 'describe your ideal lead' interface just a more polished way to run the same structured filters?from what i can read, the differentiation is in the enrichment layer. 1b+ profiles with web data layered on top of linkedin means the matching isn't limited to what's in someone's headline or job titles. if the enrichment actually captures context that structured fields miss, like conference speaking history, writing, or other signals, then natural language queries start to mean something qualitatively different. for use cases where the right person is hard to find by title alone, that's where this earns its pitch."

GMAC Member

GMA Community

"Quite useful! But if lead discovery becomes trivial with tools like this, do you think the real bottleneck shifts to outreach quality?"