The story
Why it exists and what building it taught me. Written for the homepage card, kept here in full.
Why: I wanted to see what would happen if I applied the same OpenIntelligence engine to clinical information. OpenClinic is the prototype where I tested it against chart-shaped data (not production medical software).
Clinical Data Sync: I integrated the SMART on FHIR standard using secure OAuth flows (ASWebAuthenticationSession). This lets the app connect directly to SMART sandbox endpoints and securely download structured Patient, Condition, and Medication resources.
Local Storage: Instead of sending patient histories to a cloud database, the app parses and maps the incoming FHIR clinical resources directly into local SwiftData schemas, keeping health records private and offline.
Current State: I reused the same agentic reasoning loop from OpenIntelligence, wired up SMART on FHIR discovery and OAuth (ASWebAuthenticationSession) to pull demo Patient, Condition, and MedicationRequest resources into a local model. It’s surprisingly good at finding relevant information in the chart and answering questions with citations, but the current data is too limited to be more than a demo of the retrieval and reasoning patterns. The next step would be to connect it to real FHIR endpoints and see how it handles the messiness of real clinical data, which comes with a multitude of complexities.
