Semantic Coverage – A tool to visualize RAG blind spots using UMAP
I built this because I was tired of guessing why my RAG system was failing. It projects user queries vs. documents into 2D space to find 'Red Zones' (high user intent, low documentation). Open source, built with FastAPI + React. Would love feedback on the clustering logic.
Semantic Coverage – A tool to visualize RAG blind spots using UMAP launched on December 24, 2025 with 5 votes, #2,550 of 11,628 launches that month and more than 75% of that year's launches.
What it does
Automated detection of knowledge gaps and blind spots in RAG vector stores. - aashirpersonal/semantic-coverage
The "Code Coverage" tool for RAG Knowledge Bases. Automated detection of knowledge gaps, hallucination spots, and representation bias in Vector Databases. In software engineering, we track Code Coverage to prevent bugs. In AI engineering, we ship RAG (Retrieval Augmented Generation) systems without Semantic Coverage . This tool provides semantic observability by projecting both Documents (Knowledge) and User Queries (Intent) into a shared latent space (using UMAP). It then uses density-based clustering (HDBSCAN) to identify "Red Zones"—areas of high user density but low document density. git clone https://github.com/aashirpersonal/semantic-coverage.git cd semantic-coverage # Backend Setup…from github.com
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