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Extract structured data from unstructured documents for APIs and ETL workflows.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "unstract" yet — see the docs or source repo.
Extract invoice number, vendor, issue date, tax amount, and total amount from these PDF invoices, and return a standardized JSON array. Mark missing fields as null.
A standardized invoice JSON output ready for downstream databases or ETL pipelines.
Read these candidate resumes and extract name, email, phone, education, the latest three work experiences, and core skills into ATS-ready structured data.
Structured candidate profiles with consistent fields for ATS import and screening analysis.
Extract contract ID, parties, effective date, expiration date, payment terms, and liability clauses from contract documents, and format them as API-ready JSON.
Structured contract clause data formatted for system API consumption.
Classify documents, extract fields, mask PII, and export AI-ready datasets.
Extract validated structured data from documents, scans, images, and spreadsheets.
Extract structured data from academic PDFs with natural-language querying and batch workflows.
Parse documents into structured, confidence-scored fields for automated extraction workflows.
Choose regex first, then add LLMs for low-confidence parsing edge cases.
Automate Extracta AI tasks through Rube MCP with up-to-date tool schemas.