Why REALM360 + KAOS keep showing up in health and MedTech conversations.
A pattern note from the c51 / REALM build, because health is where the cost of broken data fabric is most visible.
The failure mode that keeps repeating:
- A patient exists in an EMR with one ID
- The same patient exists in a wearable provider's cloud with a different ID
- The same patient exists in a payer's claims system with a third ID
- The same patient exists in a research cohort with a fourth, deliberately anonymised ID
- The same patient exists, ground truth, as one human being
Most MedTech AI is being built as if those four IDs already reconcile. They do not. The provider knows. The patient definitely knows.
This is the layer REALM360 is built to handle - a 360 view of the entity (patient, clinic, device, supply lot) that holds across systems with provenance intact. KAOS is the orchestration discipline underneath: identity, provenance, reconciliation, then AI.
The difference in practice:
- Wearable-to-EHR integrations stop being one-off heroics and become a repeatable pattern
- Real-world evidence (RWE) studies stop falling over on cohort definitions
- AI clinical decision support gets audit trails that regulators can actually inspect
- Cross-border MedTech deployments (which is most of the interesting work right now) become buildable instead of bespoke
The sharper way to say it:
Health AI is not bottlenecked by model accuracy. It is bottlenecked by the fact that the system underneath cannot reliably say "this is the same patient / device / event" across the touchpoints that matter.
If you're building at the wearable-EHR seam, RWE / RWD, clinical AI, or cross-border health platforms - DM open. The architectural patterns travel well.
#HealthTech #MedTech #REALM360 #KAOS #RWE #ClinicalAI