Modern data foundations for connected healthcare.
Make complex clinical and operational data reliable, accessible and ready for future services.
- EHR/
HL7/ FHIR/ CSV/ API - Ingestion and CDC
- Identity/
terminology quality - Curated FHIR and analytical stores
- Governed APIs, BI and AI services
Legacy records, inconsistent codes, duplicate patients, siloed reports and undocumented transformations make modernization risky and downstream insights unreliable.
We build pipelines and data platforms that unify structured and unstructured information across legacy applications, EHRs, HIEs and business systems. Our approach addresses migration, terminology, identity, quality, provenance, access control and ongoing operations so data can support interoperability, analytics and AI without losing clinical meaning.
How we approach it.
- Inventory datasets and consumers
- Define target models and governance
- Design batch/event ingestion
- Validate mappings and patient identity
- Reconcile migrated records
- Establish lineage, controls and sustainable operations
What it includes.
- Legacy EHR and system migration
- HL7/FHIR normalized data foundations
- Batch and streaming ETL/ELT
- Terminology and reference data services
- Patient and provider identity reconciliation
- Clinical data warehouses and lakehouses
- Data quality, catalog and lineage
- Analytics/AI-ready governed datasets
Where it fits.
- Migrate historical encounter and document data
- Create longitudinal FHIR clinical stores
- Normalize multi-EHR codes and demographics
- Move JSON and relational sources into PostgreSQL
- Build data marts for provider operations
- Prepare de-identified research datasets where lawful
- Quality-monitor inbound interface feeds
- Modernize SOAP/file pipelines into managed APIs