Monday, July 13, 2026
ProRAG Diagnostic Toolkit
A diagnostics platform that ingests a team’s existing RAG documents, query logs, and configuration, runs targeted experiments to identify the top 3 failure modes (poor chunking, embedding mismatch, contradictory sources), and provides a prioritized fix plan with measurable accuracy improvement estimates.
Target Audience
AI engineers at companies with a deployed RAG chatbot achieving only 70% answer accuracy, who need to reach 90% but lack the time to run months of A/B tests across chunking strategies, embedding models, and retrieval parameters.
Why Now
Dev.to 'Bigger Context Windows Didn’t Make Our RAG Smarter' proves that brute-force context expansion isn’t the answer; Product Hunt 'Context.dev' launched data extraction APIs for better RAG inputs, but no tool diagnoses the pipeline; GitHub 'awesome-llm-apps' shows proliferation of RAG implementations, indicating a large base of users hitting quality ceilings.
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