The data layer underneath every Toro product. FHIR R4 storage, SMART-on-FHIR auth, public APIs — standards-compliant from day one, with AI workflows that live on top.
Most "FHIR-compliant" EHRs store data in proprietary formats and translate to FHIR on export. That works for compliance checkboxes — and falls apart when AI tries to read it. Toro stores in FHIR R4 from the first byte, so every layer above gets clean, structured data.
Translation drops fidelity. AI workflows hallucinate because the data shape is inconsistent.
No translation, no fidelity loss. AI workflows operate on the same standard resources every modern healthcare system speaks.
Composable workflows that share a common FHIR data substrate. More shipping every quarter.
Toro is built to connect, by default. Public FHIR R4 API. SMART-on-FHIR backend services authentication. US Core conformant. The full conformance statement is published at /fhir/metadata for anyone to verify. Bulk Data $export and additional standards-based interop capabilities are on the near-term roadmap — we ship and document, we don’t pre-promise.
Migration in and out is a feature, not an afterthought. Switch moves practices from any major EHR — FHIR-to-FHIR for sources that support it, guided manual migration for everyone else. If you ever decide to leave Toro, the same team helps you go, in reverse.
Standards are how a healthcare platform earns trust monthly instead of trapping it.
The next decade of healthcare AI doesn't depend on bigger models. It depends on cleaner data.
Most healthcare AI underperforms because the data it reads is messy — proprietary schemas, inconsistent vocabularies, undocumented fields, lossy exports. That's the legacy EHR's fault, not the model's. When AI workflows operate on FHIR-native resources, the same models perform measurably better. Same model, cleaner substrate.
Toro is the substrate.