neomatrix369/AIE7-Demo-Day-Project
RagCheck is a proactive corpus quality assessment tool that analyses RAG application document collections before deployment, identifying content gaps and providing specific recommendations to improve query performance. The platform transforms reactive corpus fixes into proactive quality assurance, helping organisations achieve as high as 85% score.
This tool helps organizations building Retrieval Augmented Generation (RAG) applications ensure their document collections are high quality before deployment. You provide your documents and test queries, and it analyzes them to identify content gaps and suggests specific improvements. This is for AI product managers, RAG system developers, or content strategists who want to proactively optimize their RAG application's performance.
Use this if you need to assess and improve the quality of your RAG application's source documents to ensure accurate and relevant responses.
Not ideal if you are looking for a tool to evaluate a deployed RAG system's live performance rather than its underlying document corpus.
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TypeScript
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Last pushed
Oct 27, 2025
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