Hard-to-find VC & accelerator data — scraped, cleaned and published as a free Notion list

Executive Summary

Founders, investor-relations teams, boutique VC firms and service providers routinely spend days assembling up-to-date lists of relevant micro-VCs and accelerators, and many miss smaller or newly formed funds; that friction scales — there are about 1.6 million potential customers in this ecosystem, and poor data leads to wasted outreach and missed matches. The problem is worse for seed-stage founders and corporate VC teams who need granular tags (industry, check size, stage) and reliable contact predictions rather than generic fund names. You could build a scraped, cleaned and continuously enriched dataset of hard-to-find VC and accelerator records, published as a free, regularly updated Notion list to capture virality and SEO, with paid APIs, CSV exports and premium enrichment (contact prediction, firm scoring, activity signals) as monetization. Starting free lowers acquisition friction while paid tiers target an ACV of ~$3,000 to address a theoretical $4.8B market (1.6M x $3K); expect initial traction from 1–5% conversion of engaged users and enterprise pilots for higher ARR. This is attractive now because founder behavior has shifted toward data-driven targeting, the proliferation of micro-VCs increases addressable opportunities, and cheap automation plus LLMs make higher-quality enrichment and contact inference feasible; the proposal scores well on market (90/100) and revenue (88/100) given those trends and relatively medium competition. To stand out you must deliver superior freshness and transparency (timestamps, provenance), high-precision contact prediction and a low-friction Notion-first UX that encourages community contributions and link-backs, while planning for the hard realities: scraping reliability, legal/privacy constraints, verification costs and the ongoing engineering required to maintain data quality and conversion into paid usage.