Healthcare — PHI-Safe Knowledge Access + Controlled Automation

Client profile: Provider / payer / healthtech with PHI exposure

Situation

Teams wanted AI assistance (policy Q&A, operational summaries, triage support), but privacy and audit requirements demanded tight governance.

What MHN implemented (public-safe)

• Data governance: ownership, critical data elements, quality scorecards, accountability

• Identity-aware access: role-aligned boundaries for sensitive data and knowledge assets

• Governed RAG: approved sources only, traceable outputs suitable for review

• Trusted agents: controlled actions + auditability designed for regulated workflows

• CacheGuard: spend guardrails and cost predictability for high-volume queries

• One-Click SoT (GitHub → AWS): hardened deployment patterns + monitoring and evidence export

  
  

Outcomes (typical)

• Reduced privacy risk while still enabling AI productivity gains

• Higher trust from stakeholders because outputs are grounded and reviewable

• Faster operational turnaround with governance controls in place

• Controlled cost profile (no runaway AI spend)

  
  

CTA: Request a PHI-safe pilot blueprint (sanitized) and evidence template.

Note: These examples are anonymized composites and may combine elements from multiple engagements to protect confidentiality.