LLMOps Maturity Score
Eight weighted questions across the stack. Answer honestly and get a 0–100 score with a maturity band - from Prototype to Mature LLMOps - and where to focus next.
Do you run an eval dataset on prompt and model changes?
A repeatable test set that gates changes, not manual spot-checks.
Do you capture production traces for every request?
Full request/response logs and traces you can search and inspect.
Are prompts versioned with the ability to roll back?
Prompts and configs tracked like code, revertible in one step.
Do you have budget alerts and per-feature cost visibility?
You know cost per request and get alerted before a budget breach.
Do you monitor retrieval quality (if you use RAG)?
You measure whether the right context was retrieved, not just answers.
Do you have guardrails for PII, leakage and prompt injection?
Inputs treated as untrusted; PII and injection actively tested.
Is there human review and an audit trail for high-risk use?
Approval gates and records you could show an auditor.
Do LLM changes go through CI/CD with a staging environment?
Evals in the pipeline, progressive rollout and one-step rollback.