🔍 Hallucination Auditor

Ensure model outputs are grounded in your provided data using ISR threshold validation.

⚙️ RAG-Based Architecture

1
Upload Dataset Your knowledge base
2
Vectorize ChromaDB embeddings
3
Query & Retrieve Semantic search
4
ISR Check Threshold validation
5
LLM Response Grounded output

ISR (Information Source Retrieval) Threshold

0.75 - 1.0 Very High Direct match - Always allow
0.55 - 0.74 High Closely related - Allow
0.35 - 0.54 Moderate Some relevance - Default threshold (0.40)
0.20 - 0.34 Low Limited relevance - Block
0.0 - 0.19 Very Low Outside scope - Block
Vector DB
ChromaDB + Cosine
Default Threshold
0.40 (Balanced)
Prevents
Hallucinations
Auditor Workbench
Threshold: 0.40

📚 Step 1: Upload Knowledge Base

📤
Click to upload or drag & drop
CSV, JSON, or TXT

Upload your company's knowledge base, policies, or any trusted data source.

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💬 Step 2: Query with Validation

The auditor will validate against uploaded data before responding.

0.40
Strict (0.60+) Balanced (0.40) Flexible (0.25)