What it is (plain English)
Reads documents - invoices, forms, PDFs, emails - and pulls the important fields out as structured data a workflow can use, with a human check where confidence is low. It removes the manual data-entry step at the front of many processes.
Problems it solves
- Staff manually keying data off invoices, forms, and PDFs.
- Slow, error-prone intake of unstructured documents.
- Automation that stalls because the input is a document, not data.
What must exist first
Platform Core Setup. Extracted data typically feeds a Workflow Studio process, so pairing with automation is expected. Do not assume a trained field-extraction use case provides arbitrary full-text extraction; prove the selected document type, extraction output, and review threshold in the target instance.
What the customer needs to provide
- Representative sample documents (the messier and more varied, the better for training).
- The fields you need extracted and where they flow next.
- Accuracy expectations and the human-review threshold.
- Volume estimates by document type.
Where it can go next
Feeds Workflow Studio and RPA-driven processes; unlocks straight-through processing for document-heavy workflows (AP, onboarding, claims). When extracted data will feed an AI agent, send only the bounded text and minimum metadata approved for that use case. Keep source binaries and unrelated record context outside the agent boundary.