Managed Evals & Observability

Overview

Models change behavior. Source documents go stale. User queries shift. Costs creep. The team that built your AI hands you a runbook and moves on. We don't — this is the retainer that keeps your production AI working, year after year.

Honest about fit

A fit if…

You shipped a production AI system — built by us or someone else — and need ongoing quality discipline
Your CEO or board wants a monthly observability report on AI performance and cost
You don't want to staff a full internal AI quality team but still need the discipline of one

Not a fit if…

You need 24/7 NOC service or sub-1-hour SLAs — we're not an MSP
Your system has no eval harness or gold set — we'll build those first (separate engagement)
You want a feature factory under the banner of "retainer hours" — features are scoped separately

What you get

Concrete deliverables. No hand-waving.

Daily automated eval runs against your gold set, with regression alerting
Weekly retrieval-quality review (Standard tier and above)
Monthly observability report: cost, latency, accuracy, adoption, incidents, recommendations
Quarterly business review with your sponsor — what's working, what to evolve
Model-update management — every new Claude, GPT, or Gemini is eval-gated before production
Gold-set evolution — ~20 new questions per quarter, sourced from real failure cases
Incident response within SLA, on the eval/observability platform you already run