Healthcare data, in motion.
Lab systems, diagnostic platforms, and secure pipelines that move healthcare data at scale without losing the audit trail. We do the unglamorous integration work and the new platform work, on the same engagement.
Updated
- Streaming
- Ingestion · Real-time and batch
- Sub-second
- Query path · Hot reads, indexed
- Validated
- Quality gates · Schema and rule checks
- Petabyte
- Scale · Storage architecture
Three substrates,
one foundation.
From lab systems to genomic platforms, the same engineering team handles ingestion, processing, and reporting. The work is delivered by our forward deployed engineers, who build it once, instrument it properly, and hand you the keys.
Laboratory information systems
Comprehensive LIMS for clinical labs, research facilities, and diagnostic centers. Specimens in, validated results out, with the audit trail your accreditor expects.
- Sample tracking and chain of custody
- Test result processing and validation
- Quality control workflows
- Instrument integration
- Regulatory reporting
- PostgreSQLprod
- Redisprod
- HL7prod
- LOINCprod
- SNOMED CTprod
Diagnostic data platforms
Platforms that process, analyze, and report diagnostic data across modalities. Imaging, pathology, genomics, biomarkers, on a single substrate.
- Medical imaging pipelines
- Pathology workflows
- Genomic data processing
- Biomarker analysis
- Clinical decision support
- DICOMprod
- HL7 FHIRprod
- Apache Kafkaprod
- Elasticsearchprod
- TensorFlowprod
Data processing pipelines
Scalable, secure infrastructure for healthcare data workflows. Real-time streams and batch jobs that don't collapse the first time volume doubles.
- Real-time data streaming
- Batch processing
- Validation and cleansing
- Format transformation
- Automated reporting
- Apache Airflowprod
- Sparkprod
- Kubernetesprod
- AWS Lambdaprod
- Dockerprod
Specialized for the
data shape.
Platforms shaped to the data they hold. Lab systems behave differently from imaging archives, which behave differently from genomic stores. We respect the difference.
Clinical laboratory systems
End-to-end lab management from specimen collection to result reporting.
- Specimen tracking
- Test ordering
- Result validation
- QC management
- Billing integration
Diagnostic imaging
Imaging data management and analysis platforms, modality to read.
- DICOM storage
- Image processing
- AI-assisted reading
- Reporting tools
- PACS integration
Genomic data platforms
Secure processing and analysis of genomic and precision medicine data.
- Variant analysis
- Population studies
- Clinical genomics
- Data sharing
- Privacy controls
Population health analytics
Large-scale health data analytics for population health management.
- Cohort analysis
- Risk stratification
- Outcome prediction
- Public health reporting
- Epidemiology
We speak the protocols.
Industry-standard formats for interoperability and compliance. FHIR R4 where the system supports it, HL7v2 and CDA where it doesn't, DICOM and VCF where the data demands.
Clinical data
Standardized clinical data exchange and terminology.
- HL7 FHIR
- HL7 v2
- CDA
- LOINC
- SNOMED CT
Imaging data
Medical imaging standards and interoperability protocols.
- DICOM
- IHE
- WADO
- XDS
- PIX / PDQ
Laboratory data
Laboratory data management and quality standards.
- LIS
- LOINC
- ASTM
- CLSI
- CAP
Genomic data
Genomic data formats and sharing standards.
- HGVS
- VCF
- FASTA
- GA4GH
- ClinVar
Healthcare data,
properly held.
PHI requires more than a checklist. Encryption at every layer, controls scoped to least privilege, and an audit trail that holds up under examination.
Data encryption
End-to-end encryption for data at rest and in transit.
- AES-256 encryption
- Key management
- Secure transmission
- Zero-trust architecture
Access controls
Granular access controls and audit logging.
- Role-based access
- Multi-factor auth
- Audit trails
- Session management
Compliance
Built-in compliance with healthcare regulations.
- HIPAA compliance
- GDPR ready
- SOC 2 Type II
- FDA validation
Data challenge, described in plain English.
Tell us what the system is supposed to do, what it does today, and where the gap is. We'll write back with a read on what to build first. For a brownfield proof point on AdvancedMD, see our RCM and clinical workflow automation case study.