Session state
Knows whether the underlying exchange is open, closed, in pre-market, or approaching a scheduled event.
PRE-TRADE INTELLIGENCE FOR TOKENIZED EQUITIES
Nocturner scores the risk of a tokenized stock trade before it executes—combining market state, oracle freshness, liquidity, price divergence, and unpriced news.
Reference price can no longer defend execution.
CATALYST DETECTED / 03:14 UTC New 8-K classified as material. Not yet reflected in oracle mid.
01 / THE GAP
When the closing bell rings, onchain markets keep moving. Reference prices age. Spreads widen. Depth disappears. Breaking news changes fair value—with no circuit breaker and nobody watching.
02 / FIVE SIGNALS. ONE DECISION.
Nocturner turns fragmented market conditions into one inspectable score and a decisive execution verdict.
Knows whether the underlying exchange is open, closed, in pre-market, or approaching a scheduled event.
Measures how old the reference price is and escalates when the market is moving faster than the feed.
Compares your order to actual pool liquidity—not a headline TVL number that disappears on execution.
Tracks the distance between the token, oracle mid, and the underlying equity's last defensible close.
Reads filings, halt notices, corporate actions, and news that may not be reflected onchain yet.
THE VERDICT SYSTEM
Conditions are inside policy limits.
Execution cost or divergence is elevated.
Reference data can no longer defend the price.
Policy rejects execution until conditions recover.
Thresholds shown are illustrative while calibration is in progress. Production policy is configurable per user, agent, and protocol.
03 / AI WHERE IT MATTERS
AI finds and structures the information a threshold cannot see. Every execution decision remains deterministic, auditable, and reproducible.
Our design principlesMonitors filings, earnings wires, halt notices, and material overnight news before stale liquidity can react.
Turns splits, dividends, mergers, ex-dates, and delistings into a structured, continuously maintained calendar.
Translates plain-English limits into deterministic, auditable guard rules. The model drafts; the contract decides.
Learns normal spread, depth, and volume signatures by session, then surfaces deviations static thresholds miss.
Turns raw factors into a clear reason a person—or another agent—can inspect before acting.
Backtests weights against realized outcomes so risk policy can improve as market structure changes.
04 / ONE ENGINE, FOUR SURFACES
Clear scores, factors, and overnight context for retail traders.
For humansImmediate risk changes and overnight gap reports for active traders.
See deliveryA native risk query and dry-run endpoint for autonomous agents.
For agentsTrades that breach policy revert at the session-key level.
See enforcement05 / ARCHITECTURE
The separation is deliberate. Probabilistic systems discover context and compile intent. Deterministic infrastructure owns the final decision around capital.
06 / BUILDING IN THE OPEN
Collecting historical conditions and exposing transparent factors before enforcement.
Policy simulation and MCP-native verdicts for agent developers.
Session-key enforcement after thresholds are proven against real outcomes.
EARLY ACCESS / 2026
We're opening the read-only scorecard first while the engine collects the history needed for responsible calibration.