Use Case

Healthtech & Digital Health

In digital health, privacy is an architectural obligation. We build and audit patient management systems, telemedicine platforms, and clinical automation where medical records are strictly isolated and AI agents operate without leaking sensitive data.

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The problem

Clinics and Healthtech startups face a unique technical challenge: they need to innovate rapidly with AI and telemedicine, but operate under strict regulations (like HIPAA). A flawed access control (IDOR) in a patient portal exposes medical histories, destroying reputation and generating massive legal liability.

Our solution

We isolate data at the database level using Row Level Security, ensuring a patient can only ever view their own data regardless of server code vulnerabilities. We audit AI pipelines to ensure LLMs can assist with diagnostics and scheduling without the technical capacity to exfiltrate PII.

Capabilities

Multi-tenant architectures for clinics with strict isolation of patient records and test results
Authorization audits (IDOR, BOLA) in patient portals and telemedicine APIs
Implementation of private AI pipelines for clinical automation (triage, scheduling, protocol RAG) without data leak risks
Technical control validation for regulatory compliance (HIPAA / local health privacy laws)
Auditable observability systems: immutable logging of who accessed which record and when

Innovation in Healthtech cannot come at the cost of patient privacy. That’s why we design security in layers: if a vulnerability in the Node.js or Python backend allows an unauthorized query, the RLS policy in PostgreSQL blocks access at the data layer. That is the difference between a patch and security by design.

Your critical infrastructure deserves an honest technical assessment.

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