Measurement & Readiness

The Problem

You deployed an AI chatbot, but you have no idea if your knowledge base can actually answer the questions customers ask. Bad answers erode trust faster than no answer at all. Most teams discover gaps only after customers complain.

The Solution

Automated RAG evaluation tests your knowledge base against real and synthetic customer questions. Get a readiness score, identify weak areas, and know exactly where to improve — before your chatbot goes live.

How It Works

Generate

Create synthetic test cases from your support data and documentation

Evaluate

RAG Triad assessment: answer relevance, context relevance, groundedness

Score

Readiness score with triage classification for every failing answer

Key Capabilities

RAG Test Cases

Synthetic and real question-answer pairs for comprehensive coverage

Assessment Classification

Triage labels identify root causes: retrieval fail, hallucination, context miss

Readiness Scoring

Weighted metrics produce a single readiness score for your knowledge base

Retest Workflow

Verify improvements with automated retesting after documentation changes

73%

Ticket Reduction

2.3×

Faster Resolution

$127K

Annual Savings

Why Averas for Measurement?

Industry-standard RAG Triad evaluation methodology
Automated test case generation — no manual question writing
Actionable triage labels, not just pass/fail scores
Built-in retest workflow to verify improvements

Assess Your Knowledge Base Readiness for AI