Who funds you is on file.

Drop a pitch deck PDF and get a ranked shortlist of the VCs and angels most likely to back you, scored on check size, stage fit, sector match, recency of activity, and named past investments. The database covers 32,000+ investors across 7,000+ firms.

Sources: SEC EDGAR Form D, Y Combinator, OpenVC, Wikidata, firm websites.

How matching works

A four-stage pipeline. First, the parser extracts your company name, sectors, target stage, and round size from your PDF. Second, a SQL recall stage retrieves the top candidates from an index of 32,823 investors. Third, an LLM rerank stage scores thesis fit against your round. Fourth, four deterministic sub-scores (check_fit, stage_fit, recency, and sector evidence count) are computed in Python and surfaced as auditable signal alongside the LLM ranking.

What the database covers

  • 32,823 investor profiles with sweet-spot check size, range, and sector focus
  • 7,279 firms with thesis text scraped directly from their websites
  • 11,718 named past investments with company, stage, date, and round size
  • SEC EDGAR Form D filings (90,146 named related-party records, 36-month rolling window)
  • 5,813 Y Combinator companies from the Algolia index
  • 8,478 Wikidata-enriched company records
  • 2,073 firm thesis texts scraped from firm websites

Who is this for?

Pre-seed through Series B founders raising in the US, EU, or globally, across any sector: AI, fintech, biotech, hardware, climate, consumer, devtools, security, robotics, space, agriculture, and more. You get a ranked shortlist of investors with the right check size and sector adjacency, plus links to their named past portfolio companies so you can verify thesis fit yourself.

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