We need our own eval system
For teams that need their own evaluation system
Teams building agents who cannot measure whether a change made the agent better or worse.
What usually goes wrong
- "It feels off" is the only quality signal
- Every prompt fix breaks something else
- LLM judges nobody has checked against people
The questions that matter most for you
Recommended path
- Step 1Eval Readiness AssessmentPilot: Procedure designed and deliverable with existing tools, but not yet delivered to a client. Sold under pilot terms.One week to see where your agent fails today and what evaluation system you need.Access: Transcripts under a data agreement.Scope and limits →
- Step 2Golden Dataset & Rubric WorkshopPilot: Procedure designed and deliverable with existing tools, but not yet delivered to a client. Sold under pilot terms.Facilitated sessions where your experts define "good" and we turn it into rubrics and a labeled seed set.Access: Sample outputs under a data agreement.Scope and limits →
- Step 3Eval SetupPilot: Procedure designed and deliverable with existing tools, but not yet delivered to a client. Sold under pilot terms.We build your own evaluation system in your stack, with tools you own.Access: Repository, CI and transcript access.Scope and limits →
- Step 4Fractional AI Quality LeadPilot: Procedure designed and deliverable with existing tools, but not yet delivered to a client. Sold under pilot terms.An ongoing advisor who owns your evaluation strategy, reviews releases and reports monthly.Access: Release notes and dashboards.Scope and limits →
Evidence you can inspect now
- What Eval Setup builds, step by step, and what you own afterward
- How calibration metrics are defined (coverage, missed failures, agreement)
Links: sample report · how it works · trust & data
Next step
Tell us about your agent. You will get the right starting point and the access it needs, whether or not it is a paid service.
Book a scoping call