AI RAG Audit Readiness Assessment

Make your RAG system audit-ready before production.

A focused 2-3 week assessment for teams that need to prove whether their RAG answers are grounded, privacy-aware, policy-aligned, and reviewable by compliance stakeholders.

Assessment Output

A clear risk picture and a practical production path.

Executive risk summary for leadership review
Grounding and unsupported-claim findings
PII/PHI leakage test results with sample cases
Policy compliance and control-gap notes
Audit evidence package sample
Why this matters

Your RAG system may work. The question is whether you can prove it is safe.

Unsupported Claims

Answers can include rates, policy details, or operational claims that are not supported by retrieved context.

PII and PHI Leakage

Retrieved context can surface customer, patient, or employee identifiers directly inside model output.

Weak Audit Evidence

Teams often have logs, but not the evidence needed to explain why an answer was allowed, blocked, or changed.

Scope

What we assess

The assessment focuses on the operational controls that matter when RAG moves from prototype to production.

Grounding quality
Unsupported claims
PII/PHI leakage
Policy compliance
Audit log quality
Tenant/data boundaries
Failure behavior
Pilot readiness
Engagement

A clear process, not an open-ended consulting project.

01

Discovery

Review the RAG workflow, data sources, policies, user groups, and production goals.

02

Risk Testing

Run representative prompts for grounding, privacy, policy, jailbreak, and failure-mode checks.

03

Evidence Review

Inspect what the system records today and what would be missing during an audit.

04

Briefing

Deliver findings, recommended controls, and a pilot path for HardRAG or your internal stack.

Start with audit-only confidence.

The safest first step is to evaluate your RAG system without blocking users, then decide which controls belong in production.

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