TICKET MANAGEMENT
Daily SLA-Breach Forecast Accuracy Scorecard to Slack
Once a day, compares yesterday's breach predictions against actual outcomes, computes precision and recall of the forecast.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily in the morning
- ActionRead yesterday's forecast snapshots from PostgresPostgres
- ActionPull actual breach outcomes from FrontFront
- LogicJoin predictions to outcomes, compute precision/recall
- OutputPost accuracy scorecard to SlackSlack
What it does
Closes the loop on the forecasting engine by grading how well yesterday's predictions matched reality, surfacing where the model under- or over-warned so thresholds can be tuned.
When to use it
When you rely on breach forecasts to drive escalation and rebalancing, and need to trust them. Use this to keep the prediction logic honest and catch drift before it costs you SLAs.
How it works
- 1A schedule fires once each morning.
- 2Reads yesterday's logged forecast snapshots from Postgres.
- 3Pulls the actual resolution and breach outcomes for those same tickets from Front.
- 4Joins predictions to outcomes and computes precision, recall, false-alarm rate, and the count of unpredicted breaches.
- 5Identifies the worst misses, breaches the forecast never flagged, with the signals it had at the time.
- 6Posts a formatted scorecard to Slack and writes the daily metrics row back to Postgres for trend tracking.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect FrontShared inbox, conversations.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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