Independent AI-observability risk assessment for enterprise systems in regulated verticals. 3-6 weeks. Board-ready deliverables. Reproducible methodology.
Your AI systems don't fail on the metrics you're watching. They fail silently — retrieval collapses onto stale documents, routers pick confusable neighbor sections, confidence distributions flatten, prompt libraries drift week over week. Traditional accuracy metrics move last. By the time the number changes, the regulatory exposure is already priced in.
Silent failures don't show up in dashboards. They show up in OCR letters, DOI examinations, SEC inquiries, and bar-complaint filings.
This audit finds them first.
The audit is framed as a regulatory-readiness risk assessment. Vertical scope determines the framework overlay:
Clinical decision support, EHR AI, prior-auth, radiology, patient-facing chat, drug-interaction systems.
HIPAA + FDA AI/ML Guidance + State laws
Credit decisioning, fraud detection, algo-trading, robo-advisory, AML surveillance.
SR 11-7 + OCC + SEC + FINRA + NYDFS + CFPB
Rating, pricing, claims triage, fraud detection, adverse-action decisioning.
NAIC AI Model Bulletin + State DOI + Colorado SB21-169
Contract review, litigation support, e-discovery, legal research, brief drafting.
ABA Rules 1.1/1.6/3.3/5.3 + State Bar UPL + Privilege + FRE
Seven deterministic sensors + proprietary multi-sensor consensus orchestration + confounding-signals-style temporal root-cause analysis.
Arithmetic over signals your pipeline already produces. Same inputs in, same numbers out, every time. Runs continuously; no LLM calls internal to the audit engine.
Proprietary orchestration layer applies N-LLM consensus across the sensor catalog to identify root causes, not just symptoms. Divergences between sensors surface as flagged findings for human review.
When multiple sensors alert, the earliest-alerting sensor is the causal suspect; later-alerting sensors are downstream effects. 13-turn documented advantage over single-sensor investigation.
All sensor code is MIT-licensed and open source. Client can independently reproduce findings post-audit. The orchestration layer is proprietary; findings that rely on it are noted.
Four audience-tier written deliverables plus two live briefings plus a 60-day post-engagement check-in.
2-page governance-ready summary. Fit for board / board committee / executive sponsor consumption. Findings + regulatory exposure + management's proposed remediation posture.
5-10 pages for VP / CTO / CAIO consumption. Findings by severity, risk ranking, prioritized 30/60/90-day remediation plan.
30-50 pages for the AI engineering team. Per-system findings, root-cause chain reconstruction, sensor output data, code-level remediation guidance where applicable.
10-20 pages. 90-day observability roadmap: which sensors to deploy, calibration guidance, threshold tuning, escalation ladder, governance model.
Executive briefing (2 hours, up to 8 attendees) + Technical deep-dive session (3 hours) for Client's AI engineering team.
Post-engagement review of remediation progress + deployment status + any new findings. Written summary memo delivered within 5 business days of the check-in call.
Depending on scope: number of AI systems, compliance framework layering, delivery mode, timeline compression.
Milestone-based invoicing: 30% initiation / 40% midpoint / 30% final. Net-30 payment terms. Payment via Stripe direct link, ACH, or Client AP system.
No financial interest in Client's AI systems, vendors, or model providers. No affiliate relationships. No revenue-share arrangements.
Professional Liability (E&O) at $1M per occurrence / $2M aggregate is standard for engagements. Certificate of Insurance provided at engagement kickoff.
Client data handling: Data stored on encrypted workstation only; never uploaded to third-party services; deleted within 30 days of engagement completion. Business Associate Agreement (BAA) executed for HIPAA-covered engagements.
30 minutes. No obligation. If we're a fit, next step is discovery questionnaire.
Request discovery call Explore the sensor catalogcontrarianAI is not a law firm and does not provide legal advice. Deliverables reference regulatory frameworks for client-orientation purposes. Client-specific regulatory analysis should involve Client's counsel and, where appropriate, external regulatory counsel.