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RAG and context

RAG Retrieval Debugger

Diagnose why your RAG system retrieves wrong or irrelevant context. Analyze embedding similarity scores, query-document relevance, and retrieval ranking quality. Identify whether failures are caused by chunking, embedding model selection, similarity thresholds, or query formulation.

Run RAG Retrieval Debugger Interactively 100% client-side execution in your browser. Zero data retention.
Open Interactive Tool

What Problem RAG Retrieval Debugger Solves

Production AI deployments require predictable token economics, rigorous parameter verification, and deterministic schema handling. RAG Retrieval Debugger isolates parameters client-side before payloads hit third-party foundation model APIs.

Primary Production Use Cases

  • Debug why RAG returns wrong context for specific queries
  • Improve retrieval precision for domain-specific content

Security & Data Privacy Considerations

All computations execute locally in browser memory. No prompt payloads, test inputs, or secret credentials are ever retained or stored on central servers.

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