Real-time latency dashboards, feature-level drift detection, and auto model refresh on configurable thresholds - no SRE team required.
Real-time latency dashboards and feature-level drift scoring alert you within 60 seconds of a threshold breach - before users are affected. When drift turns critical, automated retraining and promotion kick in without any manual intervention.
Every request processed by your deployed model is instrumented automatically - no SDK changes required. Latency (p50 and p99), requests per second, error rates, and throughput are streamed to live dashboards. You see the pulse of your model in real time, not in yesterday's batch log.
Incoming inference data is scored against the training distribution on a feature-by-feature basis using statistical distance measures (KL divergence, Population Stability Index). When any feature drifts beyond your configured threshold, an alert is dispatched - to Slack, PagerDuty, email, or webhook - within seconds, giving your team a head start before impact reaches users.
When drift severity crosses the critical threshold, the platform triggers an automated retraining workflow using the latest production data. The refreshed model passes through the validation quality gates and is promoted to replace the degraded version - all without manual intervention. Your model stays current as the world changes around it.
Latency percentile charts update live with every inference request. Drill into p99 spikes by time window, endpoint version, or input segment to isolate the root cause before users notice slowdowns.
Statistical distance between live inference data and the training baseline is scored per feature, continuously. Catch distribution shifts in individual input dimensions before they accumulate into model-level degradation.
Set drift thresholds, latency SLOs, and error-rate limits. Alerts fire within 60 seconds of breach - delivered to Slack, PagerDuty, email, or any webhook. No custom alerting rules to maintain separately.
When drift breaches the critical tier, a full retraining and promotion pipeline fires automatically. No on-call engineer required - the platform keeps your model current without manual intervention.
Every drift event, alert, and model refresh action is logged immutably with timestamps and triggering data. Satisfy model governance requirements and provide evidence for regulatory audits without extra effort.
Monitor every deployed model endpoint - across cloud, VPC, and on-premises - from a single unified dashboard. Compare health across environments and spot cross-endpoint issues in seconds.
Start monitoring your deployed models in real time today. No credit card, no instrumentation work, no additional infrastructure.