@so_ainsight: Messy documents transform into structured knowledge with a single command. When feeding documents to AI, one quietly to…

Messy documents transform into structured knowledge with a single command. When feeding documents to AI, one quietly tough issue is the problem of "searching but not getting the desired information back." Many AI document tools just split documents into pieces and run searches on them. Whether accuracy improves is up to luck. That's where Hyper-Extract comes in. An Apache 2.0 OSS tool that converts unstructured text into a structured knowledge base. It's not just a PDF splitting tool. Nor is it merely a wrapper to boost search accuracy. Hyper-Extract pre-organizes text so AI can immediately pull up knowledge graphs, time-series data, and spatial information. There are 8 types of knowledge structures it can convert to. → Knowledge Graph (graphing connections between information) → Hypergraph (structuring complex many-to-many relationships) → Time Graph (tracking changes over time series) → Spatial Graph (organizing location and positional relationship info) → Spatiotemporal Graph (structuring along both time and location axes) → Typed Data Model (output as structured data) → Obsidian Vault (convert to Markdown notes in wikilinks format) → MCP Knowledge Base (queryable directly from Claude or IDE) The task of "repeatedly searching documents to find target info" can now become a "knowledge base convertible once for repeated high-accuracy referencing." Especially for organizing papers, structuring financial reports, and knowledge management of private documents, the user experience should feel dramatically different. You can verify with numbers too. → 80+ YAML templates (for finance, law, medicine, industry, general use) → Equipped with 10+ extraction algorithms like GraphRAG and LightRAG → Supports both OpenAI and Claude, local execution possible with vLLM → Start instantly from YAML templates with no code needed Implementation is simple too. uv tool install hyperextract ・Free (Apache 2.0, commercial use OK) ・Complete locally with vLLM (possible without external API dependency) ・Directly referenceable from Claude or IDE via MCP Over 2,400 GitHub stars make sense. Official repo link below.