The Kepler Insights API exposes the same scoring engine that powers Kepler’s Pro Insight and Pro Venture portals — over a stable REST surface, with deterministic schemas and a free sandbox.Documentation Index
Fetch the complete documentation index at: https://docs.keplerinsights.us/llms.txt
Use this file to discover all available pages before exploring further.
What it scores
Every Kepler score is a composite over 67 signals organized into 4 buckets:| Bucket | What it measures |
|---|---|
| Team & Structure | Founder track record, team strength, structural differentiation |
| Market Position | Sector tailwinds, market size, competitive landscape |
| Momentum & Tailwinds | Regulatory environment, press coverage, brand strength |
| Financial Health | Revenue, funding efficiency, employee growth |
KI-5 (early-stage) to KI-1+ (elite franchise). A separate scale premium (up to ~12 points) lifts established mega-caps whose fundamentals justify a higher tier than their growth-stage signals alone would produce.
What you can do with it
- Score one company on demand.
POST /v1/scorereturns inline if a record is cached for your tier; otherwise returns 202 + a job to poll (cold scoring typically settles in 25–90 seconds). The SDKs handle the polling for you. - Track score history.
GET /v1/score/{domain}/historyreturns the full time-series — every scoring run for that company. - Compare against a cohort.
GET /v1/company/{domain}/cohortreturns sector + geo + profile-matched peers, ranked. - Assess data confidence.
GET /v1/company/{domain}/confidenceshows how much of the score is grounded in real data vs neutral fallbacks. - Read the universe.
GET /v1/distributionandGET /v1/moverssummarize every company Kepler has ever scored.
How it costs
Cached calls are nearly free; cold calls cost us real money on fetchers + LLM enrichment. Pricing reflects that asymmetry — see Economics for the rationale.Get started
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