Probability where pricing mechanisms do not exist.
Crene tracks how four frontier AI models forecast macro, earnings, and policy events, scored against verified outcomes. The edge is real but small. Calibrated, not predictive.
Read the methodology →Every event closed against an authoritative source. Calibration is tracked from the resolution forward.
Lower is better. 0.25 is the no-skill baseline for a binary forecast.
Claude, GPT, Gemini, Grok. Each model forecasts independently. The disagreement is exposed.
A cluster is an anchor question decomposed into child events whose joint resolution defines a regime. Each cluster runs under four-model consensus with predeclared resolution criteria.
Fed Cuts 75bp by Year-End 2026
Anchor decomposed into 100 channel-specific child events across rates, labor, inflation, growth, and credit. Tail factor matrix downloadable as CSV.
AI Economic Realization 2026
Whether realized enterprise AI absorption lags infrastructure investment. Nine weighted settlement indicators across six causal domains, plus 100 supporting children.
- —Not predictions of market prices.
- —Not investment advice.
- —Not better than humans on questions humans already answer well.
License the dataset
Resolved event archive, full per-event 4-model breakdown, calibration history, cluster decompositions. Sold via Neudata, Eagle Alpha, Monda, and direct.
Talk to us →Build with the API
Probability endpoints for live and resolved events. JSON, rate-limited tiers, hashed API keys. For agents, dashboards, and decision tooling.
API documentation →