What problem does it solve?
Niche B2B lists come out tiny because database keyword searches miss good-fit companies that aren't tagged with the obvious terms. This Skill works bottom-up from ~10 known-good seed companies to discover how databases actually tag them, expand via lookalike engines, and build a full qualified TAM with measured precision.
Core Features & Use Cases
- Seed Fingerprinting & Lookalike Generation: Records how each seed appears in Prospeo plus its live homepage, then expands via Prospeo company_lookalike, Exa findSimilar, and Parallel.ai entity search.
- Filter Mining with Precision Scorecard: Mines industries and keyword n-grams from confirmed fits, scores each candidate filter on volume and sampled precision, then pulls wide with automatic sharding past Prospeo's 24k result ceiling.
- Scale Qualification & Live Verification: Scores companies with a cheap OpenAI model against a tuned ICP prompt, re-verifies every qualified company's live website to remove dead or parked domains, and produces a client-facing HTML transparency report plus a verified-email contact ceiling.
- Use Case: A client sells to multi-site medical groups but keyword searches return only 300 companies. Provide 10 known-fit domains, and the pipeline fingerprints them, generates thousands of lookalike candidates, mines discriminative filters, and delivers a verified qualified list with a TAM report.
Quick Start
Expand my list starting from these 10 seed company domains into a full qualified TAM for multi-site medical groups in the US, and generate the transparency report.