.NET 10 Engine in Active Development

Stop fighting
relational dependencies.

RapidFHIR is a decoupled ELT pipeline engineered for the reality of legacy healthcare data. Ingest raw FHIR payloads at maximum network speed, process them asynchronously, and flatten them into a highly optimized SQL schema for real-time analytics.

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Built for the Enterprise Reality

We don't build operational apps. We build the high-speed bridge that gets your data out of isolated APIs and into your analytical data warehouse.

Analytical SQL Power

FHIR APIs are excellent for transactional software, but crawling endpoints is too slow for PowerBI and machine learning. We flatten deeply nested JSON into hardened, query-optimized relational tables for instant analytical access.

Microsoft Native

Hospital networks and medical device ecosystems run heavily on the Microsoft stack. Built entirely on C#, .NET 10, and SQL Server, our engine drops seamlessly into your existing enterprise IT infrastructure.

Taming "Dirty" Data

Real-world HL7 and FHIR bulk conversions are rarely perfect. Our architecture anticipates out-of-order deliveries and broken foreign keys, utilizing smart automated stubbing to keep the pipeline moving without dead-letter queues.

How RapidFHIR Works

Traditional synchronization forces worker threads to wait on relational database inserts. We split extraction and loading into two asynchronous pipelines.

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1. High-Speed Extraction

The Ingestion Worker pulls data via smart watermarks and streams raw JSON directly into a Cosmos DB document store, bypassing C# serialization for absolute maximum network speed.

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2. Event-Driven Routing

The Change Feed automatically detects new payloads and wakes up a separate background thread. Data is deserialized and mapped into domain entities without ever blocking the upstream API calls.

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3. Smart Dependency Resolution

SQL Stored Procedures utilize automated stubbing logic. If an Encounter arrives before its Patient, the database generates a lightweight stub to satisfy constraints immediately.