Building UniHealth Nexus: A Case Study in Medical AI Architecture
Healthcare AI requires balancing technological velocity with strict patient privacy regulations. Here is the story of how we built UniHealth Nexus.
The Scoping Challenge
UniHealth needed a unified patient intake and video consultation portal. The core requirement was clear: zero exposure of Patient Health Information (PHI) to public AI models.
HIPAA-Compliant Database Isolation
We built the database with AES-256 encryption-at-rest and configured AWS KMS key rotators. All data sent to AI models is pre-processed to scrub names and medical IDs, utilizing strict private proxies.
Integrating with Legacy EHR Systems
Legacy Electronic Health Records (EHR) use archaic data exchange formats. We built custom microservices that ingest and map patient scheduling logs directly into HL7-compliant REST APIs.
Building UniHealth Nexus proved that compliance doesn't have to slow down development. With structured scoping and senior architects, we shipped the platform in 10 weeks.
Pankaj Kumar Malhi
Founder & Lead AI Architect
Pankaj is an AI systems engineer specializing in secure Retrieval-Augmented Generation (RAG) vector pipelines, multi-tenant cloud gateways, and fast Next.js SaaS platforms.
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