Unstract

Active
GitHub Python AGPL-3.0

Description

LLM-driven extraction of unstructured data, built for API deployments and ETL pipeline workflows. Automates document parsing, PDF extraction, and intelligent data processing with LLM-powered intelligence.

Key Features

  • Prompt Studio defines document extraction schemas with natural language
  • Supports REST API deployment and ETL pipeline workflows
  • MCP Server integration connecting to Claude and other AI agents
  • Compatible with OpenAI, Anthropic, Bedrock, Ollama, and more
  • Handles PDFs, images, scans, and many other document formats
  • n8n node integration to embed into existing automation workflows

Use Cases

πŸ’‘ Extract structured data from unstructured documents for database storage
πŸ’‘ Automate document processing in finance and insurance workflows
πŸ’‘ Build intelligent extraction systems for KYC and compliance scenarios
πŸ’‘ Convert unstructured PDF reports into analyzable JSON data

Tags

data-processing rag python automation llm workflow

Categories

πŸ“š RAG Tools πŸ”„ Workflow

Quick Start

1. Clone the repository and navigate to the project directory
2. Run `./run-platform.sh` to start everything
3. Visit `http://frontend.unstract.localhost`
4. Login with username `unstract` password `unstract`
5. Define extraction schemas in Prompt Studio and start extracting
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