Predictions

A prediction is the AI’s forward-looking signal that a pattern is likely to recur within a given window. Predictions let you act before an incident happens rather than responding after the fact. Predictions are generated automatically from active and emerging patterns. Each prediction carries a probability score (0–1), an impact level, and a time window.

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The Predictions screen

Navigate to Predictions in the left sidebar. The top-bar action area contains a window selector (7 d / 30 d / 90 d) that controls the data range shown across all panels.

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Summary tiles

Four KPI tiles appear at the top of the page: These figures come from GET /v1/predictions/summary.

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Risk signals table

Below the tiles, a table lists the top predictions by probability. Each row shows:

• Pattern name — links to the pattern detail page
• Probability — score from 0.00 to 1.00, displayed as a percentage
• Impact — critical, high, medium, or low
• Window — the prediction time window in days (e.g. 5D WINDOW)
• Status pill — whether the prediction is active or dismissed

Click any row to navigate to the corresponding pattern or to provide feedback on the prediction.

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Composite risk forecast chart

The forecast chart is an interactive time-series showing the workspace-wide composite risk score over the selected window. It combines:

• Observed series (solid line) — historical composite risk from confirmed incidents
• Projected series (dashed line) — AI extrapolation beyond today
• Alert threshold line — horizontal dashed line at your workspace’s alert probability (default 70 %)
• Breach marker — a labeled point where the projection crosses the alert threshold

The forecast data comes from GET /v1/predictions/forecast. You can scope the chart to a single pattern by passing pattern_id.

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Probability matrix

The probability matrix is a 5 × 5 heat grid that maps likelihood (rows, bottom-to-top: Rare → Almost Certain) against impact (columns, left-to-right: Negligible → Severe). Each active prediction is plotted as a signal dot in its corresponding cell. Cell colors range from green (low risk) through amber and red to dark red (critical). The matrix gives you a portfolio view of where your risk is concentrated.

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Model accuracy panel

The model accuracy panel shows how well the prediction model is calibrated: The accuracy data comes from GET /v1/predictions/accuracy. The eyebrow label (e.g. EVAL 06·06) shows the date of the most recent model evaluation.

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Alert rules panel

The alert rules panel displays the active alert rules for this workspace. Each rule shows its name, threshold, time window, and delivery channels. Use the toggle switch to enable or disable a rule.

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Filtering predictions

Use the query parameters on GET /v1/predictions to filter the list:

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Providing feedback

After an event window closes, you can tell Causeloop whether a prediction was correct. This feedback is used to improve the model over time.

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Dismissing a prediction

If a prediction is no longer relevant (for example, the trigger event was cancelled), you can dismiss it via PATCH /v1/predictions/{id} with dismissed: true. Dismissed predictions are hidden from the default list view but remain in the audit trail.

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API reference

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Related pages