Company intelligence, from what they're hiring.
Search any company for its live hiring signal — velocity, momentum, the themes it over-indexes, its tech stack and where it's building. Primary-source, updated continuously, zero contact data.
Live triggers
Companies hiring one theme far above the market rate — the why-now signal, ranked by lift.
Hiring for m&a / integration activity at 27.5× the market rate — 4 roles, 31% of its live openings.
Hiring for data/ai transformation at 10.5× the market rate — 77 roles, 79% of its live openings.
Hiring for security build-out at 10.0× the market rate — 3 roles, 25% of its live openings.
Hiring for security build-out at 7.5× the market rate — 3 roles, 19% of its live openings.
Hiring for m&a / integration activity at 7.5× the market rate — 3 roles, 8% of its live openings.
Hiring for security build-out at 6.8× the market rate — 6 roles, 17% of its live openings.
Hiring for m&a / integration activity at 6.2× the market rate — 3 roles, 7% of its live openings.
Hiring for data/ai transformation at 6.0× the market rate — 5 roles, 46% of its live openings.
Hiring for data/ai transformation at 5.9× the market rate — 4 roles, 44% of its live openings.
Hiring for data/ai transformation at 5.6× the market rate — 26 roles, 43% of its live openings.
Hiring for data/ai transformation at 5.3× the market rate — 4 roles, 40% of its live openings.
Hiring for data/ai transformation at 5.3× the market rate — 4 roles, 40% of its live openings.
× (lift) = the company's share of live roles in a theme ÷ the corpus base rate. A trigger fires at ≥1.8×. Bars scale to the top lift on the board; counts and shares come straight from live postings.
Zero contact data — and that's the product.
How this works. Every signal derives from primary job-posting data collected continuously from company ATS systems — hiring velocity from posting timestamps, tech adoption from role requirements, comp bands from k≥12 anonymised cohorts. Numbers refresh with each build; each panel shows its own as-of date.