Evaluate stage
Best for
Any team that has to prove a model is ready, whether to itself, to auditors, or to customers.
How it runs
Turn business goals into measurable pass/fail criteria for each task.
Golden datasetLabelled cases that represent your real workload, frozen and versioned.
Automate scoring, then check how well the grader agrees with human reviewers before trusting it.
Grading harnessLLM-as-judge and programmatic checks that run in minutes, not days.
Probe the model with adversarial prompts, jailbreak libraries, and abuse cases specific to your domain.
Red-team reportTranscripts, severity ratings, and mitigations for injection, leakage, and misuse.
Wire the suite into CI so every retrain is scored the same way.
Release gateA pipeline step that blocks any version that regresses on the metrics you care about.
In practice
Numbers from the base model versus the model we shipped.
Generic models produced fluent summaries that omitted or invented findings, so clinicians rewrote most of them.
Clinician acceptance
Before: 58%After: 86%
Unsupported findings per 100 notes
Before: 7.1After: 0.9
FAQ
Yes. Evaluation is often our first engagement. We can benchmark your current prompts, a vendor's model, or an in-house fine-tune on the same scorecard.
On every model or prompt change, plus a weekly check against a fresh sample of live traffic to catch drift.
Often paired with
Share a sample of your data and a target metric. We'll come back with a plan and a timeline.
We reply within one business day (IST).
