HIPAA-compliant AI for healthcare practices

The consumer versions are not. Free ChatGPT and consumer Claude offer no Business Associate Agreement, and prompts can be retained and used to improve models. Pasting protected health information into them is a HIPAA violation.

The path to HIPAA-compliant AI is a deployment covered by a BAA with training and retention disabled — for example Claude or OpenAI models running through Azure OpenAI under Microsoft's BAA, or Anthropic's API with zero data retention. We build on those tiers, never the consumer apps. More on building a HIPAA AI chatbot without exposing PHI.

Yes. We work under a Business Associate Agreement when we touch protected health information, and we architect every integration so the AI model itself is covered by a BAA with the provider (for example Azure OpenAI under Microsoft's BAA). No PHI ever flows through a service that lacks BAA coverage.

We deploy on enterprise and API tiers with model training disabled and zero data retention configured, so prompts and responses are not stored by the provider or used to train models. PHI stays inside your BAA-covered environment, access is scoped, and every AI interaction is written to an append-only audit log.

Where confidentiality requirements rule out any third-party processor, we deploy private or on-prem models so nothing leaves your infrastructure. See the difference between Claude Team and the API on data retention.

Yes. We build direct API and FHIR integrations into EHR and practice-management systems including Healthie, DrChrono, SimplePractice, and athenahealth. The AI reads and writes through your existing system rather than copy-paste, and data stays inside your BAA-covered environment. We have studied the Healthie integration surface in depth and done the platform homework on its API and webhooks.

Simple integrations and automations start at $1,700. Custom builds run $17K to $53K depending on the number of workflows, the systems we connect, and the depth of compliance architecture required.

The discovery call is free and includes a draft scope and a rough quote. The only paid pre-build step is a $2,420 audit, and only when an existing system needs a rewrite or rescue — credited toward the build. Book a 30-minute call to walk through what your practice actually needs.

4 to 8 weeks for the build phase, plus 8 weeks of embedded support. The support phase matters because most AI pilots fail without structured implementation help. We stay embedded during rollout to ensure adoption.

No. We integrate with the EHR and practice-management system you already run. The AI layer connects to your existing tools through APIs and FHIR. No migration, no disruption to clinical workflows.

Every integration we build includes a mandatory human verification layer. AI-generated output — clinical summaries, draft notes, intake categorizations, billing codes — is flagged for clinician or staff review before it is acted on or entered into the record. AI never writes to the chart unsupervised.

Audit trails log every AI interaction, every source referenced, and every human approval. That verification layer is what makes the system safe for a clinical setting.

The highest-value uses we ship are clinical document automation (drafting notes, summaries, and letters from your templates for clinician review), patient intake automation (routing, categorizing, and pre-populating records), AI-assisted medical billing (suggesting codes and flagging denials for staff review), and document search across your records. Each one is a real integration into your EHR, not a standalone chatbot.

Yes. For practices whose confidentiality requirements rule out any third-party AI processor, we deploy private or on-prem models where the model runs on infrastructure you control and no PHI leaves your environment. This works with any LLM, not just Claude, and is the strongest possible posture for protected health information.