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Governed AI evaluation platform
A production evaluation and policy layer for generative AI features across multiple product teams.
Problem
Teams shipped generative features without a shared evaluation harness, making quality and safety reviews inconsistent.
Context
Anonymized B2B product company introducing AI assistants into customer workflows.
Architecture
Central evaluation service, prompt/version registry, offline + online eval jobs, and policy hooks before promotion to production.
Engineering challenge
Balancing developer speed with mandatory evaluation gates that product teams would actually use.
Security considerations
Secret handling for model providers, PII redaction in traces, and access control on evaluation datasets.
Implementation
Platform team delivered SDKs and CI templates; security co-owned the promotion checklist.
Results
Cut promotion incidents related to prompt regressions and established a measurable quality baseline per assistant.
Lessons learned
Evaluation must be a paved road, optional tooling is ignored under deadline pressure.
Technology
- Python
- Kubernetes
- Feature flags
- Observability stack
- Vector retrieval