Retab

Retab

Retab builds document automation infrastructure for AI-native companies.

We help teams turn unstructured documents — PDFs, emails, scans, spreadsheets, and images — into reliable structured data and production workflows. Retab combines document parsing, schema-based extraction, classification, splitting, editing, validation, and human-in-the-loop review in one system.

Unlike black-box extraction tools, Retab makes every workflow run inspectable. Teams can see the source document, intermediate steps, extracted fields, validation results, and execution traces. This makes document automation easier to debug, test, version, and improve over time.

Retab is designed for builders operating at the edge of AI automation:

• Extract structured JSON from complex documents
• Build document workflows as versioned graphs
• Add human review where confidence is low
• Run regression tests on prompts, schemas, and models
• Compare workflow changes with experiments before shipping
• Expose document workflow context to AI agents through MCP

Our view is simple: document workflows are software. They should be observable, testable, versioned, and operable by both humans and agents.

Website: retab.com
Docs: docs.retab.com
GitHub: github.com/retab-dev