The data layer every healthcare AI solution needs.
AXIFI Data Infrastructure ingests from any EHR, normalizes to FHIR R4, enforces tenant isolation, and serves structured clinical data to AI workloads in under 200 ms — without a data engineering team.
Built on the Synaptis trust layerHIPAASOC 2 Type IIFDA 21 CFR Part 11Trust Center
Healthcare data is everywhere. Usable healthcare data is rare.
The average health system has 18 distinct clinical data sources producing data in 9 different formats. AI models require clean, normalized, computable data. The gap between raw EHR data and AI-ready data is a multi-year engineering project — one that most organizations cannot staff or afford to build in-house.
- HL7 v2, C-CDA, FHIR R4, proprietary EHR APIs, DICOM, X12 — same data, 6 different formats
- 63% of AI pilot failures in healthcare are attributed to data quality, not model quality (JAMA AI, 2023)
- The average healthcare data pipeline takes 18–24 months and $2–5M to build and maintain
- HIPAA, HITECH, and state-level data laws create compliance overhead that delays every project
Ingest anything. Serve everything. Stay compliant by design.
Universal ingest
AXIFI connects to EHRs via certified FHIR R4 APIs, HL7 v2 feeds, C-CDA documents, claims files, lab interfaces, and device streams. New sources are onboarded in days, not months.
Normalization to FHIR R4
Every inbound record is normalized to FHIR R4 using clinical terminology mapping (ICD-10, SNOMED CT, LOINC, RxNorm). Terminology gaps are surfaced to your clinical informatics team for review.
Tenant-isolated storage
Data is stored in a tenant-isolated environment — your data never co-mingles with another organization's. All data at rest is AES-256 encrypted. All data in transit is TLS 1.3.
AI-ready serving layer
The AXIFI Data API serves normalized FHIR resources, patient timeline views, population cohort queries, and streaming event subscriptions — all in under 200 ms, with full audit logging.
The infrastructure numbers that matter.
ms median query response time
FHIR R4 resource fetch, p95 < 450ms
Uptime SLA
multi-region, active-active architecture
EHR systems supported natively
including Epic, Cerner, Meditech, CPSI
Time to production data pipeline (weeks)
What is inside Data Infrastructure.
Universal ingest layer
Connects to any clinical data source. Pre-built adapters for 18+ EHRs. Custom adapters delivered in 2–3 weeks for non-standard sources.
FHIR normalization engine
Maps every inbound record to FHIR R4 with SNOMED CT, LOINC, RxNorm, and ICD-10 alignment. Terminology drift is monitored and reported.
Compliance layer
HIPAA BAA-covered environment. De-identification pipeline for research and analytics workloads. PHI access logs retained 7 years.
AI serving API
RESTful FHIR R4 API plus a SQL-compatible analytics interface. Supports streaming subscriptions for real-time AI workloads. SDK in Python and TypeScript.
Connects to the entire clinical data ecosystem.
- EHR (certified)
- Epic (SMART on FHIR)
- Cerner (CDS Hooks)
- Meditech Expanse
- CPSI
- Azalea Health
- +13 others
- Lab / pathology
- Quest Diagnostics
- LabCorp
- Hospital LIS (HL7 v2)
- Point-of-care devices
- Claims / payer
- CMS Blue Button 2.0
- EDI 837/835
- CommonPayer FHIR
- Carequality bulk FHIR
- AI / ML
- Hugging Face Inference API
- Azure OpenAI Service
- AWS Bedrock
- Custom model endpoints
- LangChain / LlamaIndex
Common questions.
Ready to deploy Healthcare Data Infrastructure in your environment?
See how Synaptis fits into your stack — no generic demos, just your workflow.