Define Success Once. Let the Platform Enforce It.

Set a threshold — accuracy above 90%, sync lag under 2 hours, fewer than 5 failed jobs. Linearvis watches it around the clock, triggers a remediation action the moment it's breached, then re-checks 30 minutes later to confirm the fix worked.

The Problem: Metrics degrade silently between manual reviews

Model accuracy drifts for days before anyone notices and re-trains
Data freshness SLAs are tracked manually, not enforced automatically
Remediation is reactive: by the time you fix it, downstream decisions were already wrong
No feedback loop to know whether the fix actually worked

The Solution: Continuous monitoring with verified auto-remediation

Agent Goals watches your live metrics 24/7, breaches trigger automatic actions — re-run predictions, trigger syncs, pause failing jobs, or send alerts — and the system re-measures 30 minutes later to confirm the fix worked.

22+ Live Metrics Prediction accuracy, data freshness, failed job count, governance health, and more — all tracked continuously

Threshold Breach Detection Configurable above/below/gte comparators with per-goal thresholds for every metric

Auto-Remediation Re-run predictions, trigger data syncs, pause failing jobs, or send branded alert emails — your choice

Verified Outcomes The system re-measures 30 minutes after every remediation action and records whether it worked

Event-Driven Waking Goals watching freshness or governance metrics wake immediately when a sync or governance scan completes

AI Goal Creation Describe your goal in plain English — AI maps it to the right metric, threshold, and remediation action automatically

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