Find out where your AI breaks in production.

~10 questions, branched by your stack and scale. A specific score for each category that applies to you — plus your two weakest areas and what to fix first.

what we measureonly the categories that apply to your architecture

Provider Resilience

How your stack survives upstream LLM failures — the #1 outage cause in 2026.

Evaluation & Quality

Whether you can detect a regression before users do — or only after.

Retrieval Quality

if applicable

RAG is only as good as what it retrieves — and most teams never measure this.

Cost Visibility

if applicable

LLM bills doubled to $8.4B in a year. Most teams discover their burn at month-end.

Agent Reliability

if applicable

Multi-step agents fail up to 75% of the time on simple tasks without proper state design.

Incident Response

if applicable

Generic SRE runbooks miss every AI-specific failure mode. You need new ones.

"95% of AI pilots fail to deliver measurable returns. The 5% that ship have one thing in common — they treat it as production engineering, not prompt engineering."

— mit study, august 2025