Self-discovering leading-indicator engine — mining cross-vertical event chains for validated "A precedes B" rules.
Honest by design. Day-1 history is thin, so most chains will read "need more history" or "weak" until the event log deepens. We never present a low-confidence correlation as certain — every rule carries n, base rate, lift, and a Wilson 95% lower bound.
How it works
Ingest time-stamped events across 6 verticals (USAspending, SEC EDGAR, NIH RePORTER, ClinicalTrials.gov, CPSC, FDA) into one unified temporal log.
For each candidate chain A → B, test whether A reliably precedes B (same entity) within N days, at rate P, with lift over base rate.
Backtest on the historical log; keep only rules clearing min-sample + Wilson-bound > base-rate.
Emit live predictions for entities that just triggered an A-event.
Event log(last ingest 2026-08-05T18:01:08.747Z)
Vertical
Events indexed
usaspending
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