Rapid AI System Audit

The audit reads the traces your pipeline already emits — no GPU, no extra model calls, no new infrastructure. The five sensors are pure deterministic measurement: same inputs, same output, every time. They're MIT-licensed and stay with you — cheap enough to keep running on every request long after the audit ships. You're not buying a second stochastic layer to babysit your model. You're buying a permanent instrument on the outside of it.

Deliverables, not deliberations. Everything listed below ships within 48 hours of data handoff.

All 5 Bell Tuning sensors run against your data: context-inspector, retrieval-auditor, tool-call-grader, predictor-corrector, audit-report-generator

8-12 page PDF report with bell curves showing the shape of your AI's data flow

Silent bugs found, sorted by type, with severity scores and real examples from your data

Ranked fix list (3-5 items), ordered by effort and impact

30-minute Zoom walkthrough of findings

7 days of Slack / email Q&A after delivery

Your search/retrieval setup, or read-only access to your AI pipeline

10-20 sample queries that look like what real users ask

A small sample of your knowledge base (1,000-10,000 chunks)

30-minute kickoff call to confirm scope

Any existing eval test data you already have (optional, useful)

Standard accuracy metrics (precision@K) miss all of these. They show up in the shape of your data before users start complaining.

Clock starts at data handoff, not at purchase. Kickoff call same day.

Your team is already running an AI system in production that pulls info from a knowledge base or coordinates multiple agents

Users are reporting "plausible-sounding but wrong" answers

Your test suite still passes, but the quality feels off

The knowledge base has grown a lot since you launched, or the agent system has gotten more complex

You need a defensible, numbers-backed read before making a bigger decision (rewriting the system, switching to a new embedding model, full rebuild)

Looking for implementation labor (this is diagnosis, not remediation)

Under $10k annual AI budget (this is $2,500; the remediation work that follows costs more)

$2,500 flat. 48-hour turnaround. Two slots open this week.

Pay now Discuss fit first

Not sure if your setup fits? Email first; we'll confirm fit before you pay. Full framework: Bell Tuning manifesto + whitepapers + open-source sensors

The five Bell Tuning sensors are MIT-licensed and free. Install with npx contrarianai-context-inspector --install-mcp. If you want to run them yourself, you don't need this audit.

The audit exists for teams that want the analysis done for them in 48 hours with a defensible report attached. You're paying for the turnaround, the read of what the sensor output means, and the ranked fix list — not the tools themselves.