A rubric the model actually follows
Explaining your criteria simply is easy. Getting a model to apply them the way your experts do is not. Every ambiguity in the rubric becomes a judgment call the model makes without you.
An LLM judge your experts would sign off on.
Bring unlabeled outputs and a one-sentence rubric. Sutro surfaces the cases where models disagree, learns your quality bar from expert feedback, and hands you a calibrated, deployable AI Function.
LLM-as-a-judge works. Calibrating it is the hard part.
Pass or fail on agent traces. Quality grades on RAG answers. Policy checks on generated content. Using a model to grade outputs is the only evaluation approach that keeps up with production volume; human review doesn’t scale, and string metrics can’t read.
But a judge is only useful if it agrees with your experts. Out of the box it reflects the model’s defaults, not your quality bar. Closing that gap means building everything around it:
Curated ground truth
Agreement with your experts is the only score that matters. Proving it takes the right examples: hard cases worth an expert’s time, not a huge sample of easy calls.
Calibration that holds up
Models update, prompts change, data drifts. An agreement rate you measured last quarter says little about the judge you’re running today. Recalibration is a process, not a task.
Building an AI Function isn’t about scaling general intelligence. It’s about teaching a model exactly how your organization wants a task performed. A judge is the purest case: you teach your quality bar on the hardest examples, and we handle the rest.
Focus on scaling your judgment, not grading the grader.
Unlike eval products that stop at monitoring, Sutro shapes behavior from your feedback rather than just measuring it. The judge you build is a deployable function, not a dashboard.
Run it yourself
- Hand-write the judge prompt and iterate on vibes
- Sample outputs and label them to estimate agreement
- Re-validate every time the model or rubric changes
- You own the eval pipeline, and its maintenance
- Great for quick one-off checks and research
Let Sutro run it
- Bring unlabeled traces or outputs and a one-sentence rubric
- Annotate only the cases where models disagree
- Judge prompt optimized against your experts’ calls
- You get a deployable, portable AI Function
- Great for judges your team must trust in production
“Sutro saves our team countless hours, and it gives us the invaluable ability to measure, optimize, and prevent regressions against our domain expertise. It’s a must-have for serious AI developers.”