AI Reliability Audit

Find and Fix Hidden Failures in Your AI System in 7 Days

We instrument your production LLM workflows, analyze real traces, and identify 3–5 concrete failure modes like hallucinations, regressions, and silent breakdowns. Then we implement guardrails and alerts to reduce the risk of user-facing AI incidents.

For teams already running LLMs in production.

Book a 20-minute call

If we don’t find at least 3 real issues or meaningful risks, you don’t pay.

Engagement snapshot

7 days

Instrument, analyze, and harden your system.

3–5 failure modes

Documented issues with evidence, impact, and remediation paths.

Guardrails live

Validation, retries, and alerts in place before handoff.

Trace replaylive evidence

trace_id=4938a env=prod service=assistant

llm_call → parse_output

error: invalid_json

retry → success

guardrail: triggered

alert=incident_opened severity=critical

Designed for CTOs, Heads of AI, and engineering teams already shipping LLM-powered workflows.

The risk

Hidden failures stay invisible until customers feel them.

Production LLM systems often fail in ways that never surface as obvious errors. This audit isolates the exact failure surfaces before they become user-facing incidents.

Silent failures

Errors that never throw, but quietly degrade outcomes and customer experience.

Impact: Erodes trust without triggering obvious alerts.

Hallucinations

False answers or invented facts that make it into production responses.

Impact: Creates costly rework and escalations downstream.

Broken automations

Tool calls fail, retries loop, and workflows stall without clear visibility.

Impact: Missed SLAs and manual recovery drain engineering time.

Undetected regressions

Model or prompt changes shift behavior without obvious warnings.

Impact: Quality drops before anyone can tie it to a change.

Prompt + model drift

Small changes compound until the system behaves differently than expected.

Impact: Gradual degradation that chips away at product reliability.

Audit my system for these failures

What you get

A reliability upgrade, delivered in one week.

Every deliverable is concrete, documented, and tied to real traces from your production system.

Full trace visibility across critical LLM workflows

No more digging through logs to find a single failure.

3–5 documented failure modes with evidence

Know exactly where your system breaks and why.

Guardrails deployed on critical paths

Reduce repeat incidents without constant monitoring.

Alerts configured for future reliability issues

Catch regressions before customers report them.

Incident replay showing how failure propagates

See the exact path from trace to user impact.

This is not a report. It’s a working system with guardrails in place.

How it works

Instrument. Analyze. Harden.

A focused 3-step engagement designed to surface risk quickly and harden what matters most.

Step 1

Instrument

Instrument your AI workflows so the critical paths, handoffs, and failure surfaces are visible.

Step 2

Analyze

Review real traces to identify concrete failure modes and understand where risk is accumulating.

Step 3

Harden

Implement guardrails and alerts to reduce the risk of user-facing AI incidents.

Guarantee

If we do not find meaningful issues, you do not pay.

If we do not find at least 3 real issues or meaningful risks, you do not pay.

Pricing

Typical engagement: $8k–$12k

Fixed-scope audit focused on immediate reliability outcomes, with documented findings, guardrails, and alerts.

Includes full failure analysis, guardrail implementation, and incident replay.

Design partnersLimited availability

Limited early-stage slots at $5k

Same audit, same depth. Limited design partner slots available for teams willing to move quickly and provide tight feedback during rollout.

Check design partner availability

Ready for a reliability reset?

Book a 20-minute call to scope the audit.

We’ll confirm fit, scope the audit, and map the fastest path to a 7-day engagement.

Check design partner availability