Most "intent data" in B2B sales is inferred: web visits, job-post scraping, hiring signals. Useful, but noisy — you're guessing at a company's internal state from the outside.
SEC Form D filings are different. Any US company raising a private round (equity, debt, or fund interests) has to file one with the SEC — and it becomes public days to weeks before the funding gets a press release or a TechCrunch writeup. It's not an inference, it's a legal fact, and it's free to read on EDGAR.
The catch: EDGAR's full-text search is built for compliance people, not for a sales team trying to build a Monday-morning target list. Raw filings mix in real operating companies with investment funds, SPVs, and amendments that aren't real "someone just got money" events.
So I built a small pipeline that:
- pulls new Form D filings + funding-news RSS daily
- filters out funds/SPVs/amendments (the noise)
- scores what's left 0-100 on "how sales-ready is this raise"
- optionally enriches with company domain, industry, and generic contact emails
It ships as a plain REST API with a free tier (delayed signals, no card required) and a small dashboard to browse the freshest raises without writing any code: https://fundingsignals.net
Also just added: a free embeddable JS widget (one script tag → live "recently funded" list for VC blogs/directories) and permanent monthly archive pages for anyone who wants the historical data without hitting the API.
Curious if anyone else here is using public filings (Form D, 10-K/10-Q 8-Ks, etc.) as a signal source instead of the usual scraped/inferred stuff — what have you built with it?
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