I’ve been working on an AI tool focused on solving a real, high-risk problem in healthcare compliance.
It’s called CompliAssistant™ — an AI designed to give clear, structured guidance on HIPAA compliance and review documents like BAAs, policies, and workflows.
It focuses on:
• reliable HIPAA Q&A
• safe, filtered responses (no hallucinations)
• document review with flagged risks
• turning complex regulations into actionable steps
The hard part has been building an AI that stays accurate and conservative in a domain where mistakes aren’t acceptable.
If anyone here is working on AI for regulated industries (healthcare, finance, legal, cybersecurity), I’d love to swap insights — especially around safety architecture, prompting, and trust-building.
Happy to share the approach and offer early access to anyone curious.
Looks like a tough space. Curious where your logic breaks most often. In my own flows, missing or inconsistent fields usually create the biggest headaches.
Totally agree — missing or inconsistent fields cause the biggest wobble in any compliance flow. In CompliAssistant™ the hardest cases are workflows where the user mixes PHI and non-PHI fields without labeling them, or where the same field means different things in different systems.