Type a natural language query into Goldilocks—it scans 865 million professional profiles. This isn't a typical LinkedIn scraper dumping thousands of unvetted names. An AI agent evaluates every matched profile for actual relevance before you see it.
Describe who you want in plain English. You get scored results with full work history and verified contact details. A recruiter hunting for "machine learning engineers at Series B fintech startups in London" receives profiles assessed for career trajectory and company momentum. Context matters here beyond job titles.
Goldilocks works across 100 million companies and 50 million technologies. You can map entire account structures—see team hierarchies laid out clearly. Export to CSV when needed. Search works in multiple languages (though quality beats volume here).
Pricing runs on credits: one credit per matched result, five credits for contact info, five more for enrichments like publications or patents. Free plan includes 50 credits monthly. Paid tiers start at $49 for 5,000 credits or $249 for 30,000.
Sales teams prospecting decision-makers will find this useful. Expert networks needing niche specialists too. Revenue ops folks tired of bad data might appreciate the accuracy focus.
You won't love this if cheap bulk scraping is what you need. Credits add up fast when pulling contact details for hundreds of leads. But if bad data wastes more of your time than money? The relevance scoring probably justifies the cost. It filters before you waste hours qualifying junk leads yourself.
