Beta 0.8
AI-native access and paid evaluation
- Added stateful live-decision alerts that silently baseline each immutable forecast and notify saved-race members plus globally matching Signal Scouts on reliable WATCH/VALUE threshold crossings
- Exposed the paid locked-versus-current decision engine through a derived-only Syndicate REST resource and read-only MCP tool with fail-closed card compatibility and WATCH/VALUE trigger prices
- Added a bearer-authenticated, read-only MCP endpoint so Syndicate customers can bring current signals, derived prediction records, filtered market tapes, and prospective trust evidence into compatible AI agents
- Turned one-time API-key creation into copyable generic/OpenAI MCP connection packs with a live authenticated protocol handshake
- Added a $9 non-recurring Race Day Pass with exact-price Checkout validation, idempotent 24-hour access, delayed-payment handling, and refund/dispute revocation
- Extended pass access through interactive and background Overlay workflows, privacy controls, monthly conversion, and operator revenue telemetry
- Corrected public evidence to count one terminal revision per race and contract, then added a chronological holdout ensemble calibration lab that can never alter production weights automatically
- Closed the Syndicate webhook lifecycle with an exact derived prediction resource so every settlement event can be fetched directly without paginating history
- Turned append-only changed quotes into a paid 72-hour filtered consensus market tape for racecards, Syndicate API workflows, and signal webhook follow-up
- Added a timestamp-safe forecast read to the market tape so members can see whether the locked model-versus-consensus value gap expanded, eroded, stayed steady, or had no reliable later move
- Made decision alerts revision-aware: members hear when a qualified signal appears, strengthens, weakens, or disappears, while unchanged scheduled refreshes stay silent
- Added a paid channel-agreement lens and derived API diagnostics for the visible spread across market, ratings, and qualitative AI probabilities
