Anomaly Monitor
Spot mismatches between spot action, forecast direction, exposure logic, and event context before they resolve violently.
The live decision read
Anomaly Monitor gives the user a score, label, and explanation for where the current commodity state looks unusual. It should work as both a research aid and an alert surface.
Use the current commodity snapshot to decide whether the watchlist exposure needs research review.
A fresh price reversal, model disagreement, or catalyst miss would move this workflow route back to watch-only.
Some of the best setups start as “this makes no sense”
Professional users often monetize situations where the tape, narrative, and model logic disagree. Without an anomaly layer, that opportunity stays invisible.
Quantify the mismatch
Anomaly Monitor gives the user a score, label, and explanation for where the current commodity state looks unusual. It should work as both a research aid and an alert surface.
Preview the module on a live commodity
This workspace uses the current CommodityNode data stack and your saved workflow context so each product page behaves like a live decision-support surface instead of static brochure copy.
State vector → scenario candidates → replay evidence → review signal
Watch the active commodity move through a visible research workflow: state pressure enters the model, scenario candidates compete, replay evidence pushes back, and the review signal resolves in the center.
Current scenario snapshot ready
The decision console opens with the latest verified scenario signal, confidence, and baseline comparison, then refreshes when live model data is available.
How reliable is this scenario signal right now?
Freshness, stability, guardrails, and policy readiness are visible before a team uses the signal in a decision-support workflow.
What state is the model seeing right now?
Expose the live scenario context, state pressure, profile governance, and baseline comparison in one board so the user can audit the setup before deeper review.
See policy pressure moving across the action space
This field turns scenario-response probabilities into a living motion surface so the model feels like an active decision-support engine instead of a static table.
How does the scenario response compare with baseline policies?
Show hold, offline, PPO bootstrap, and Neural PPO side-by-side so the user can see whether the workflow route is actually better than the current baseline.
| Policy | Action | Confidence | Replay reward | Replay uplift | Walk uplift | Verdict |
|---|
Which policy survives across the full commodity basket?
Rank the active policies on the same five-commodity slate, then show the weakest commodity explicitly so the workflow route is backed by evidence instead of average-case optimism.
What is driving the current action?
Explain the strongest positive and negative drivers, then ground the workflow route with simple reason codes and comparable historical states.
What would flip this decision?
Explore how event risk, volatility, agreement, disagreement, and trend strength change the workflow route before a user commits to action.
What changed, and when?
Keep a timeline of workflow route events, profile selection changes, alerts, and replay evidence so users can audit the workflow route path instead of trusting a static score.
Operational readiness for this module
Latest decision snapshot available.
Fallback copy keeps the surface useful while live model data refreshes.
Open the linked workflow for the next decision step.
How users should read it
- Anomaly score gauge
- Mismatch explainer card
- Normal vs current pattern overlay
- Top anomaly watchlist
What this helps decide
- Great alert product.
- Complements forecasting instead of competing with it.
- Strong reason to retain paid users who want anomaly cases.
Data required
- Live change
- Forecast direction
- Agreement spread
- Event / regime context
What Pro adds to the workflow
- Free: one anomaly score
- Pro: anomaly board
- Desk: multi-commodity alerting and exports
Choose the right access level for Anomaly Monitor
Users will pay for anomaly detection when it tells them exactly when to stop trusting the easy story and start reviewing risk.
A teaser anomaly score with limited explanation.
Full anomaly monitor with context on model-vs-tape mismatches.
Escalation queue, saved anomaly states, and exportable review notes.
Cross-commodity surveillance, escalation routing, and enterprise alert feeds.
Quality standards for this module
- Explain why the score is high; score without explanation feels fake.
- Use this to trigger deeper simulator / report workflows.
- Distinguish between healthy disagreement and true anomaly.