AutoParse helps labs automate document intake and data extraction for requisitions and insurance cards, so your team spends less time retyping, chasing missing information, and reconciling records across systems.
Start with a free trial, then choose a plan based on document volume and operational needs. Plans are designed to support real lab intake workflows, not just OCR output.
Pay as You Go is best for occasional use, low monthly volume, or teams testing a narrow workflow without a subscription. Starter is typically a good fit for proving intake automation ROI with one or two document lanes. Professional fits multi-user teams that need throughput and stronger automation. Enterprise is for multi-site labs, high volumes, or strict integration/support requirements.
Start with the free trial, review the technical architecture, or contact your team for enterprise rollout planning.
Supports secure workflows and auditability; align with your compliance program and internal review.
Documents stay in private storage with controlled access instead of public links.
Launch with portal workflows now and extend into API/webhook automation as your lab scales.
When specimen volume rises, paperwork becomes the hidden throughput constraint. This platform helps labs convert paper and PDFs into structured, reviewable data.
Automated OCR + extraction reduces time spent manually keying requisitions and insurance details before accessioning and downstream processing.
Only low-confidence or missing-field records go to the review queue, helping your experienced staff spend time where it matters most.
Standardized field schemas reduce variation across shifts, locations, and temporary staff, improving handoffs to billing and reporting workflows.
Capture who uploaded, who edited, what changed, and when records were finalized or exported for stronger operational traceability.
Queue-based processing and batch uploads help labs handle end-of-day surges, outreach growth, and seasonal demand without chaotic manual triage.
Export finalized data today as CSV and evolve toward HL7 or other integration formats as your operational roadmap matures.
The platform is designed to support healthcare data handling requirements with secure storage, tenant isolation, access controls, and auditability. It can help your team build a stronger compliance posture, while still requiring your organization’s policies, risk assessments, and legal/compliance review.
Reduce repetitive data entry workload so your team can handle growth without scaling admin effort linearly.
See where records are stuck: uploaded, processing, review-required, finalized, or export-ready.
Human review queue protects data quality while still accelerating the majority of records.
Start with CSV exports and APIs now, then extend into deeper LIMS/EHR integrations later.
If your team is comparing competing platforms, use an operations-first scorecard focused on lab outcomes, not just OCR demos.
Can non-technical staff quickly review, correct, and finalize records with clear audit history and role controls?
How well does the platform handle requisition forms, insurance cards, and the variation your senders actually produce?
Look for tenant isolation, private storage, signed access, audit logs, and support for your HIPAA program requirements.
Confirm what is available now (CSV/API/webhooks) and what the roadmap is for HL7/LIMS/EHR integration.
Make sure pricing can align to your document volume, rollout phases, and multi-site operations instead of a one-size model.
Leaders should be able to see queue status, failures, review bottlenecks, export activity, and usage trends without asking IT.
“Operations wants faster intake. QA wants accuracy. Compliance wants traceability. IT wants clean integration paths. A strong document automation platform should support all four without forcing a fragile custom workflow.”
Automate the repetitive work. Keep humans in the loop for quality. Maintain an auditable process.