Services · 01 of 04
Most teams have traces. Far fewer have evidence.
The hardest question in agentic AI is not “can we build it” but “did it work.” Stoa Labs designs and implements outcome-level evaluation systems for agentic workflows: success criteria defined with the people who own the outcome, representative test populations, calibrated judges with documented limits, release gates, and the operational signals that say when trust should contract.
You end with evidence you can defend, owned by your team.
01 · 1-2 weeks
The entry point
Evaluation Baseline
A fixed-scope diagnostic for one workflow whose owner cannot currently tell whether it worked. We define outcome-level success criteria with the domain owner, construct an initial representative evaluation population, and measure the workflow against it.
It ends with measured results, an evaluator validity review including judge bias and blind spots, and a prioritized plan for closing the evidence gaps.
02 · Scoped by the baseline
Evaluation System Build
A working evaluation system, implemented and handed off: representative test populations, calibrated judges with documented bias controls, adversarial cases, release gates wired into your delivery pipeline, and operational signals with regression and rollback thresholds.
Scope, timeline, and price are fixed in the proposal from the baseline's findings. Every evaluator ships with a statement of its validity, evaluated context, and known limits.
The research behind it
This family is anchored by the lab's evaluation research: outcome scoring, judge reliability, and the operational signals that keep trust honest.
Evals, Observability & AgentOps, the research areaStart with the baseline.
Tell us about the workflow and how you currently know whether it worked.