Now turn messy documents into structured knowledge with one command.
It's called Hyper-Extract.
Most RAG tools just chunk your PDFs and hope search works.
Hyper-Extract does something much crazier:
It turns unstructured text into:
• Knowledge graphs
• Hypergraphs
• Temporal graphs
• Spatial graphs
• Spatio-temporal graphs
• Strongly typed data models
• Obsidian vaults
• MCP-ready knowledge bases
So instead of asking an AI to “read this report,” you can turn the report into an actual knowledge system.
Use cases:
→ Turn papers into research graphs
→ Extract companies, people, metrics, and risks from earnings reports
→ Build searchable knowledge bases from private docs
→ Run it locally with vLLM so your data stays on your machine
→ Query the extracted knowledge from Claude Desktop or IDE agents through MCP
It also comes with 80+ YAML templates across finance, legal, medical, industry, and general domains.
This is not just document extraction.
This is what RAG looks like when it grows a spine.
Repo: github.com/yifanfeng97/Hyper…