Platform Services
Currently ingests HL7 V2 and CCDA, normalizes and validates your data, then simultaneously produces FHIR R4 for interoperability and OMOP CDM 5.4 for research and analytics.
Who We Serve



The Pipeline
Every file goes through the same rigorous pipeline — parse, clean, enrich, convert — producing consistent, high-quality output regardless of source.
Accept HL7 V2 messages or CCDA XML documents via file upload, SFTP, FTP, or REST API. Auto-detect format from file content.
Extract structured segments (PID, PV1, OBX, DG1) from HL7 or clinical sections from CCDA. Flag malformed data early.
Standardize phone numbers, dates, gender codes, names, and admit times. AI-assisted cleaning with full transformation logging for audit.
Map cleaned data to FHIR R4 resources — Patient, Encounter, Observation, Condition, Medication, Procedure, DiagnosticReport, and more.
Simultaneously produce OMOP tables using Athena/OHDSI vocabulary resolution — person, visit_occurrence, condition, drug_exposure, measurement, observation, procedure.
Calculate completeness scores, mapping rates, and quality metrics per record. Generate per-source quality reports.
By The Numbers
Terminology Mapping Rate
OMOP CDM Tables
Input Formats (HL7 + CCDA)
User Scopes
Connectivity
Drag-and-drop file upload through the dashboard. Supports batch uploads with progress tracking and job queuing.
Automated secure file transfer. Configure host, port, path, and credentials — tested with a real connection probe before going live.
Programmatic ingestion via /api/v1/upload. Send files with organization context and receive processing job IDs.
Pull files directly from GCS buckets. Configure service account credentials and bucket paths per organization.
Connect to S3 buckets with access key authentication. Supports region configuration and path prefixes.
Ingest from Azure containers using SAS token authentication. Connection tested before activation.
Get started
Start processing HL7 messages, ensure data quality, and enable FHIR-based interoperability — all from one platform.