unstract
Reduces manual data extraction work and pipeline brittleness by automating document and unstructured data parsing at scale, cutting ETL maintenance costs and…
LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows
- Extract structured data from invoices and receipts in your document processing pipeline
- Automate field extraction from contracts and legal documents for compliance workflows
- Pull key information from unstructured logs and reports into structured databases
Reduces manual data extraction work and pipeline brittleness by automating document and unstructured data parsing at scale, cutting ETL maintenance costs and improving data quality consistency.
DevOps teams and data engineers building ETL pipelines that process variable document formats or unstructured sources.
https://github.com/Zipstack/unstract
By Zipstack
How to Get It
claude plugins install Zipstack/unstract
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me extract structured data from invoices and receipts in my document processing pipeline
Trust Signals Auto-scanned
Community Pulse New
- Show HN: Unstract(AGPL) – Launch LLM-powered APIs to structure unstructured docs — Hacker News · 25 pts
- Show HN: LLMWhisperer – Prep complex documents ready for use in LLMs — Hacker News · 12 pts
- Unstract: Open-source platform to ship document extraction APIs in minutes — Hacker News · 8 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 6,714 GitHub stars; contributors unknown; last commit 0d ago; license AGPL-3.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
- License (AGPL-3.0) may restrict commercial use. Check with your legal team.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 6,714 GitHub stars; contributors unknown; last commit 0d ago; license AGPL-3.0.