Extract Structured Data From Any Clinical Document.
Zabrizon's Document Intelligence extracts, classifies, and structures data from clinical notes, prior authorization forms, medical records, and insurance documents — with FHIR resource mapping, confidence scoring, and human review integration for accuracy-critical workflows.
What Document Intelligence Does
AI document processing purpose-built for the complexity of healthcare documentation.
Multi-Format Document Ingestion
Coming Q3 2025PDFs, images, scanned records, Word docs, and FHIR documents
Accepts any document format common in healthcare — scanned paper records, fax PDFs, digital documents, and FHIR documents — with OCR, image quality enhancement, and multi-column layout handling.
- PDF, TIFF, JPEG, Word, and plain text support
- OCR for scanned and fax documents
- Multi-column and form layout recognition
- Batch processing with API or SFTP delivery
Specialised Clinical Document Models
Coming Q3 2025Domain-specific extraction models for every healthcare document type
Purpose-trained models for clinical notes, prior auth forms, EOBs, medical records, lab reports, and referral documents — each fine-tuned on thousands of real healthcare document examples.
- Prior auth form extraction across 500+ payer formats
- Clinical note structured data extraction (SOAP, H&P, discharge)
- EOB and remittance data extraction and parsing
- Lab report, radiology, and pathology report extraction
FHIR Resource Mapping & EHR Ingestion
Coming Q3 2025Extracted data mapped to FHIR R4 resources for EHR integration
Extracted data is automatically mapped to FHIR R4 resources — Patient, Condition, Medication, Observation — enabling direct EHR ingestion without manual data entry.
- FHIR R4 resource mapping for all major entity types
- Confidence scoring per extracted field
- Human review queue for low-confidence extractions
- EHR write-back via FHIR API for Epic, Cerner, athenahealth
Why Document Intelligence Outperforms General Document AI
Healthcare documents are different. Our models reflect that.
Healthcare-Specific Training Data
Models trained exclusively on healthcare document corpora — achieving 99%+ field extraction accuracy on clinical documents where general-purpose models average 85–90%.
500+ Payer Form Templates
Pre-trained on prior authorization forms from 500+ commercial payers — automatically detecting form type and applying the correct extraction model without configuration.
Human Review Integration
Configurable confidence thresholds that route uncertain extractions to human review queues — with audit trail and reviewer sign-off for accuracy-critical clinical workflows.
Continuous Model Improvement
Human review feedback automatically retrains models — document intelligence improves with every review, achieving higher accuracy over time on your specific document types.
Connects to Your Document Sources
Ingest documents from any source and deliver structured data to any target system.
Document Sources
- SFTP / S3 Buckets
- Fax-to-Email
- EHR Document Stores
- Payer Portals
EHR / FHIR Targets
- Epic
- Oracle Cerner
- athenahealth
- Azure Health Data
Data Platforms
- Snowflake
- Databricks
- PostgreSQL
- Azure SQL
Workflow Systems
- Zabrizon Workflow Engine
- Salesforce Health Cloud
- ServiceNow
- Slack
Ready to Stop Manual Data Entry From Clinical Documents?
Join the waitlist for Document Intelligence — launching Q3 2025 with early access for design partners.