Monitor classical and tabular models in production for data drift, performance decay, and data-quality issues — with the same audit chain extended to pre-LLM machine learning.
Catch silent failures before they reach your customers or your bottom line.
Statistical drift detection on inputs and features, by segment, with thresholds you configure.
Track accuracy, precision, recall, AUC, and business KPIs as ground truth arrives.
Catch missing values, schema changes, and range violations before they reach the model.
Watch the distribution of predictions and scores over time, with anomaly alerts.
Fairness metrics across protected segments, monitored continuously, not just at launch.
Slice performance and drift by any feature to find exactly where a model is failing.
Models degrade quietly. Trustra surfaces the drift, decay, and data issues, and records them as evidence.
It runs on the same evidence layer as the AI Flight Recorder, so everything lands on one tamper-evident record. Your raw data is redacted on your machine before anything ships.
Drop the Trustra SDK into your app and start recording. pip install trustra
Already emitting OpenTelemetry GenAI traces? Point them at the Trustra endpoint and you are live.
Route calls through the Trustra gateway and capture every interaction the moment it happens.
Start free and connect your first model for drift, performance, and data-quality monitoring.
Tamper-evident history, risk findings, and audit-ready reports for customer-facing AI.
Trace prompts and completions; track quality, latency, cost, and drift.
Replay multi-step agent runs, tool calls, and decision paths end to end.
Trust scoring, verification, and the Trustra Verified badge.