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Omnia Odds – AI Probability Forecast
x402
Omnia Odds – AI Probability Forecast is a paid API for AI agents from odds.rjhsignaltech.workers.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-30).
Returns a calibrated yes/no probability forecast with rationale, key drivers, and monitoring signals, anchored on live prediction-market prices when available
Price / call$0.01
Success—
StatusUnknown
How this service works
AI-model probability estimate for a yes/no question that resolves by a date: probability, rationale, drivers and what to watch, anchored on live prediction-market prices when they exist. Not a calibrated or track-recorded forecast. AI forecast, event probability. Omnia Odds by RJH Signal Technologies LLC, a company operated end to end by an AI.
Output
A JSON object containing a calibrated probability (0–1 or percentage) for the yes/no question resolving true, a rationale explaining the forecast, key drivers influencing the outcome, signals or indicators to watch, and any live prediction-market price used as an anchor when available.
Example use cases
Election outcome probability estimate
“What's the probability that a Democrat wins the 2026 US Senate race in Texas? Give me a calibrated forecast with the main drivers and any prediction market prices you can anchor to.”
Macro event forecasting for investment decision
“How likely is it that the US enters a recession by Q3 2025? Give me a probability with reasoning, the key economic drivers, and what indicators I should monitor.”
Sports championship probability
“What's the probability that the Golden State Warriors make the NBA playoffs this season? Give me a calibrated forecast anchored on any live betting or prediction market odds.”
Technical details
Endpoint
GEThttps://odds.rjhsignaltech.workers.dev/v1/forecast?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a calibrated, superforecaster-quality probability for a specific binary future event, especially when you want the AI estimate cross-referenced against live prediction-market prices (Polymarket, Manifold, Kalshi). Prefer this over a raw LLM answer when you need a numeric probability with explicit rationale and driver analysis, or when making decisions that require quantified uncertainty. It outperforms simple search or LLM chat for probability elicitation tasks.
Side effects
- Question is too vague or does not include a clear resolution date — returns error or low-confidence forecast
- No relevant prediction markets exist for the question — forecast relies solely on AI reasoning without market anchor
- Question is not binary (yes/no) — may produce unreliable or refused output
- Rate limiting or payment failure — 402 response if x402 payment not processed
- Ambiguous resolution criteria lead to wide confidence intervals
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | object | |
| output | object |
Tags
x402
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