Workflow stages
Questions about planning, piloting, rolling out, and operationalizing document automation workflows.
OCR modernization
Move the workflow from fixed OCR templates and custom scripts to a managed process with AI extraction, classification, validation, review, monitoring, and downstream exports.
Reduce babysitting
Reduce babysitting by automating intake, routing, retries, validation, and exception queues so people only intervene when the workflow cannot confidently proceed.
New senders
Handle new senders by testing their documents against the existing schema, routing unknown formats to review, and updating instructions or workflows only when needed.
Cost savings
Turn extraction into cost savings by automating high-volume manual keying, reducing exception handling time, and measuring the operational hours avoided after rollout.
Proof of concept
A document automation proof of concept should test real intake paths, varied formats, long documents, missing fields, validation, review, and downstream export—not just clean sample extraction.
Rollout planning
Start with one high-value workflow, prove the intake-to-export process, then reuse shared patterns while tailoring fields, document types, and integrations for each team.
Internal to product
Yes. Many teams start by automating internal operations, then later expose the same extraction and workflow capabilities through productized intake, APIs, or customer-facing software.
Extractor design
Use separate extractors when document types require different fields, validation, review rules, or downstream destinations; reuse one extractor when only the layout changes.