Not predicting the next word — predicting the next world state and its market price.
REAL-WORLD EVIDENCE → EVENT PROBABILITY → PRICE DISTRIBUTION
1,284 pre-registered questions
Macro · Commodities · Equities
One forecast · Two distributions · One auditable outcome
Will a key shipping lane see a supply disruption lasting more than 7 days within the next 30 days?
First forecast: 2026-03-02 08:00 UTC · Settlement rules, evidence snapshot and price window frozen in advance.
Insurance rate & capacity anomalies · Port flow & inventory paths · Official language · Option skew
EPM-1 outputs distributions, not prose
Announcements, news, research, alternative data and evidence reliability.
Entity relations, event dependencies, transmission direction and counterfactual paths.
Price, volatility, liquidity, positioning and implied expectations.
P(Eₜ | X≤ₜ)
Event probability · Timing · Scenario weights · Conditional failure probability
P(ΔPRICE | Eₜ, MARKETₜ)
Direction · P10/P50/P90 · Cross-asset transmission · Risk contribution
A trainable forecasting stack — not a prompt chain
Compresses cross-lingual, multimodal evidence into a state that evolves over time.
Learns how entities, events and policy shocks change future states.
Outputs calibrated probabilities, occurrence windows and scenario weights.
Learns event-conditioned price paths and cross-asset transmission.
Language models handle perception and semantic compression; EPM-1's trainable representations, prediction heads and calibration layer produce the final forecast. Supports heterogeneous compute, multi-engine inference and high-availability serving.
Model-level ablation · performance follows learned forecasting capability
Continuously discovers dynamic, low-indexed, cross-lingual and vertical-domain data sources.
Owned browser and hardware environments turn complex pages and live sources into a repeatable data pipeline.
Dual timestamps, version trails, reliability scoring, deduplication and entity alignment.
Distills event states, causal paths and failure conditions instead of piling up more text.
Continuously monitors, asks, explains and revises.
Institutional systems call probabilities and price distributions directly.
Enters research, risk, procurement and positioning discussions.
Same weights, same evaluation, same event state — serving multiple workflows through different delivery surfaces.
Events, settlement, price response and error attribution.
Pre-registration, time freezing, calibration and tiered scoring.
Heterogeneous compute, private deployment, monitoring and high availability.
Products are distribution; model performance, supervision data and the evaluation system are the core assets.
Daily active users in production
Search, reasoning, prediction & tool calls
Median after key evidence appears
Over the past 90 days
Real-time evidence processing, multi-step reasoning, burst load, continuous revision and stable model serving.
9 qualified institutions in conversation · 3 defined PoVs · $1.4M potential annual contract value.
Sell model access — not another research seat
1,400 high-value institutions × $300K ACV
7,000 global institutions × $400K ACV
20–50 pre-registered questions, scored head-to-head against the client's existing process.
Priced by prediction volume, asset coverage, update frequency and model version.
Client private data, dedicated weights, single-tenant inference and independent evaluation.
Key background · A distinctive view on event forecasting · One quantifiable startup or business result
Probabilistic forecasting · Causal modeling · Training systems · One verifiable research result
Search, knowledge graphs, model serving · One production-scale result
Founding team details to be added here · Each member keeps one strongest credential and one quantifiable result.
Looking for long-term partners who understand models, financial infrastructure and enterprise distribution.
Contact the Founding Team →