Skip to main content
Deasy Labs delivers the right slice of your organization’s knowledge, ready for AI in minutes. It turns unstructured data, from a sprawling SharePoint to decades of PDFs, into the exact dataset your team is building against. Connect your storage, tag thousands of files per minute with AI-extracted metadata, slice your data any way you want, and deliver AI-ready datasets to vector databases, SharePoint, SQL warehouses, and the Collibra platform.

​
How It Works

Data Sources
Amazon S3SharePointOneDrivePostgreSQLQdrant
Connect & Ingest
OCR + source metadata
Tag
AI metadata extraction
Slice
curated datasets
Deliver
SharePointAzure SQLAmazon S3Qdrant
Maintained over time: Workflows re-ingest, re-classify, and re-export on a schedule
1

Connect

Point a Data Connector at your document store. No data migration needed.
2

Tag

Define what you want to know about your documents with Tags and Taxonomies, or let AI suggest them. Classification generates Metadata with values, evidence, and confidence for every document.
3

Slice

Build Data Slices that capture the exact subset each use case needs.
4

Deliver

Export slices to Destinations and enrich documents at the source.
5

Maintain

Schedule Workflows so datasets stay fresh as documents change.

​
Start Building

Quickstart

Go from zero to extracted metadata in under 5 minutes with the Python SDK.

Use Cases

What teams build: RAG context, compliance, document management, governance.

Cookbooks

End-to-end recipes for RAG pipelines, PII detection, and data quality.

API Reference

Every endpoint, generated from the live OpenAPI specification.

​
Why Teams Use It

Better AI Results

Curate before you compute. Retrieval works on high-quality, relevant knowledge instead of raw document dumps.

Protect Sensitive Data

Detect PII, PHI, and PCI automatically at scale and route sensitive content before it reaches downstream systems.

Reliable Over Time

Scheduled workflows keep datasets fresh, so answers stay grounded in current documents.