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Public story · 2026-02-28 · source-backed
No embeddings, no chunking. 98.7% accuracy on FinanceBench. Ships MCP integration. Leading the shift from similarity-based to reasoning-based retrieval. (GitHub)
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Replaces vector similarity search with hierarchical tree indexing + LLM reasoning. Hit 98.7% accuracy on FinanceBench — significantly outperforming traditional RAG. No chunking, no vector DB needed. Has an MCP server companion repo (pageindex-mcp) for plugging directly into co...
PageIndex gained 943 stars in a single day, hitting 29.9K total. The pitch: build hierarchical tree indexes from documents and use LLM reasoning to navigate them. No vector database. No chunking. No embeddings. The approach mimics how a human expert navigates complex documents...
What if your RAG pipeline doesn't need a vector database at all? VectifyAI's PageIndex eliminates vector databases entirely from document retrieval. Instead of chunking documents, generating embeddings, and running approximate nearest-neighbor search, it builds a hierarchical...
v0.2.16 released September 10, MIT Python, 3,141 forks, 104 open issues. It builds a hierarchical document index the model reasons over directly, skipping embeddings and similarity search (GitHub). Against the same day's data, where Milvus sits at 46,067 stars and turbovec at...
A spec is a press release until someone who didn't write it implements it. GitHub made Agent Plugins 1.0 generally available on August 12 across VS Code, Copilot CLI, the Copilot SDK, and the Copilot app on all plans. The spec, published August 6, was co-authored by AWS, Anysp...
yvgude/lean-ctx is a local binary gating what files an agent reads, persisting what it learns, and guarding what leaves the machine. Single-source and early, but the axis is right: enforcement versus suggestion. Asking a model politely not to read a secret is not a control. It...
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