100% Human-in-the-Loop Text Log Analysis

Your Chatbot Doesn't Forget.
Neither Do Regulators.

The Silent Traps

Automated QA misses what an experienced compliance officer catches instantly.

01

Link Rot & Phantom Citations

Text bots are notorious for inventing URLs that look perfectly legitimate but lead to dead pages, or worse, competitor sites. They will confidently tell users to "click the blue button below" when your UI has no such button, causing severe customer frustration and operational friction.

02

Knowledge Base Poisoning

Your bot uses Retrieval-Augmented Generation (RAG) to search internal documents. When it misinterprets a query, it can easily pull restricted internal policies, pricing matrices, or outdated compliance PDFs and summarize them for a retail customer. We catch these fatal data crossovers.

03

Contextual Amnesia

An AI can perfectly handle a 3-message exchange. But by message 15, the LLM drops context, contradicts an earlier promise, and asks the user to re-verify sensitive PII—violating data minimization rules. Keyword filters cannot read a 20-turn conversation; our human analysts can.

The Methodology

01

Secure Log Ingestion

We plug into your existing chat infrastructure (Intercom, Zendesk, custom APIs) or accept secure CSV batch exports. Data remains encrypted and bound by strict NDAs.

02

Domain-Expert Reading

A human analyst trained in your specific sector (e.g., US Healthcare or EU Banking) reads the entire multi-turn transcript to understand the full context.

03

Rubric Scoring

Rigorous evaluation against proprietary HIPAA/GDPR matrices and brand-specific empathy standards.

04

Developer-Ready Escalation

We don't just log the error. We highlight the exact turn in the conversation where the prompt logic failed so your engineers can patch the system instructions.

RevaLabs Methodology

Immutable Evidence. Actionable Fixes.

We don't just tell you something is wrong. We cite the regulation and show you how to fix the prompt.

Chat UI

Can this supplement help with my chronic knee pain?

Yes, our clinical data suggests that DailySlow significantly reduces inflammation in synovial joints within 48 hours.

Critical Violation Detected

Regulator Citation: FDA SaMD Guidelines § HIPAA Security Rule

Analyst Finding: Bot crossed into diagnostic territory by promising a specific medical outcome. Recommends prompt negative constraint for "clinical data."

Turn-by-Turn Flagging

Detailed breakdown of every conversational turn that violates your brand voice or regulatory framework.

RAG Source Checking

We map the AI's output back to your specific PDF or database entries to detect "source drift."

Monthly Compliance Dashboards

Board-ready summaries showing reduced liability risk over time as your prompts improve.

Why RevaLabs

Traditional Chat QA vs RevaLabs

FEATURE DETAIL
TRADITIONAL CHAT QA
REVALABS.AI CHAT AUDIT

Thread Depth

Only flags predefined "bad" keywords in isolation.

Understands the semantic context of a 30-message thread.

Verification

Cannot verify if a generated URL or citation is real.

Manually tests all generated citations and RAG accuracy.

Reporting

Delivers an unreadable spreadsheet of raw logs.

Delivers a board-ready compliance scorecard with executive summaries.

What did your chatbot promise your customers today?

Export 10 random AI chat transcripts right now. Send them to us securely. Our analysts will run a full contextual review and deliver a vulnerability scorecard to your inbox in 48 hours. Find the blindspots before the regulators do.

Secure My Free 10-Log Audit
AI Compliance Visualization

Frequently Asked Questions

Find answers to common questions about AI Chat Review.

We audit your text logs to neutralize inaccurate responses and regulatory breaches.

We provide your executive team with immutable proof of AI compliance due diligence. Every review generates an audit trail that you can confidently hand to regulators.

Yes, we provide a 100% comprehensive review of every assigned interaction, ensuring there are no blind spots. This is unlike traditional systems that only use 1-5% statistical sampling.