Evals for AI systems that refuse to stay static.
Agents are non-deterministic. Traditional QA breaks. We build the evaluation harnesses, regression suites, and safety checks that let you ship and iterate with confidence — even as models change underneath you.
What we offer
- →Eval suite design — pass/fail, scored, and qualitative rubrics
- →Golden dataset curation and ongoing maintenance
- →LLM-as-judge with calibrated rubrics and confidence scoring
- →Regression detection across model and prompt upgrades
- →Red-teaming and adversarial safety evaluations
- →A/B testing for prompts, retrieval, and architecture
What we believe
- Looks fine is not a quality bar. Write the eval before the agent.
- Every model upgrade is a regression risk — we plan for it.
- Cost, latency, and quality are tradeable. Measure all three.
Shipping AI without an eval harness?
Tell us about your current setup — model upgrade pain, regression bugs, hallucinations — and we'll come back with a plan.