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Hyper-Extract
Hyper-Extract is a command-line tool that extracts structured knowledge and graphs from documents using language models.
Hyper-Extract is a smart knowledge extraction command-line tool designed for researchers, financial analysts, and knowledge base managers. It ingests PDF, Word, PowerPoint, Excel, HTML, and EPUB files to generate structured knowledge through various extraction engines and templates. Users can choose from nine knowledge structures like graphs, hypergraphs, and spatio-temporal graphs across finance, legal, medical, and general domains. The system supports incremental document updates, source attribution, and exports to Obsidian vaults, JSON-LD, CSV, and GraphML. It integrates with providers such as OpenAI, Anthropic, Google Gemini, DeepSeek, Alibaba Bailian, and local vLLM deployments.
Hyper-Extract at a glance
Key features
- Rich document ingestion for PDF, Word, Excel, and more
- Nine knowledge structures including graphs and hypergraphs
- Multiple extraction engines like GraphRAG and LightRAG
- Eighty-plus YAML templates across six domains
- Incremental evolution and source provenance tracking
- Obsidian vault and GraphML export capabilities
- Interactive command-line interface for queries and visualization
- Model Context Protocol server integration
Use it for
- Turn academic papers into interactive knowledge graphs
- Extract financial entities and metrics from earnings reports
- Keep knowledge bases synchronized with changing documents
- Deploy local extraction pipelines on-premise using vLLM
Alternatives to Hyper-Extract
- AI Knowledge Graph — Extracts knowledge from documents and builds interactive, traceable graphs.
- Knowhere — It preserves page-native structures and source links for accurate agent retrieval.
- GLiNER — Enables zero-shot entity extraction without labeled training data on consumer CPUs.
- nerfguard-extract — Delivers frontier quality extraction for lower cost and faster speed.
- HyperResearch — Generates verified reports with citations checked against full source texts and a persistent vault.
- edgextract — Runs entirely in the browser with local model execution and strict data privacy.
- GraphRAG — Enhances LLM reasoning over private data using knowledge graph structures.
- DeepKE — It supports multi-modal, few-shot, and document-level extraction scenarios.
- LangExtract — It maps every extraction to its exact location in the source text.
- MinerU — Parses complex documents and tables into structured markdown for agents.
- WeKnora — Combines RAG, multi-step agents, and automatic Wiki generation in one platform.
- PageIndex — It provides 98.7% accuracy on FinanceBench without vector databases.
All Hyper-Extract alternatives