Most “AI for healthcare” guides hand you a clever local stack. The truth is simpler, and harder.
In healthcare, the model is the easy part. Compliance is the whole job.
What it actually requires
- Data on US soil. Patient data cannot leave the country.
- Encryption. Everything encrypted, in transit and at rest.
- Audit trails. Every access logged: who, what, and why.
- HIPAA coverage. The whole system has to be compliant, and provably so.
None of that is about which model you run. It is about how and where you run it.
It comes down to the provider
You do not earn HIPAA compliance by self-hosting a model in a closet. You earn it by using a provider that will sign for it.
Use a provider like AWS and get a Business Associate Agreement, a BAA. Your data then sits encrypted inside an environment already built for this. The BAA is the document that makes their infrastructure your compliant infrastructure.
Then bring in a partner who can audit your setup and give you the approved documentation that says, on paper, your system is HIPAA-compliant.
That paper is what lets you actually use it with real patients.
That is AI for healthcare. Not a model trick. A provider, a BAA, encryption, audit logs, and the documentation to prove it.
Need AI in a HIPAA setting? Book a free Gap Assessment and we will set up the provider, the BAA, and the compliance trail for you.
