🔐 BAA-eligible inference
Pre-signed BAA templates with OpenAI, Anthropic, AWS Bedrock, Google. Configured for zero data retention. Audit-logged on every call.
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HIPAA-Compliant AI Hosting for Healthcare
BAA-covered AI infrastructure for healthcare. Compliant inference paths, on-prem LLM deployment, audit logging on every model output, and zero-data-retention configuration with every major AI provider.
$25K Readiness Assessment · from $60K Compliant Cloud Buildout · from $130K On-Prem LLM · $220K+ with fine-tuning
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📌 Definition
HIPAA-compliant AI hosting is the infrastructure and engineering that allows healthcare organizations to run AI features on PHI without breaking HIPAA. Requirements: signed BAA with every AI provider in the inference path, encryption in transit and at rest, zero-data-retention configuration, audit logging on every model output, role-based access control, and override-and-audit UX on every clinical AI feature. Fixed-price tiers: $25K (4-week Readiness Assessment), from $60K (compliant cloud buildout), from $130K (on-prem LLM deployment), $220K+ (on-prem with fine-tuning). Taction has shipped HIPAA-compliant AI infrastructure with zero HIPAA findings across 785+ healthcare implementations.
HIPAA-compliant AI hosting cost · 2026
What’s included in every engagement
- Pre-signed BAA templates with OpenAI, Anthropic, AWS Bedrock, Google
- Zero-data-retention configuration verified in writing
- Encryption at rest (AES-256) and in transit (TLS 1.3)
- Audit logging on every model input and output
- Role-based access control with least-privilege defaults
- Override-and-audit UX patterns on every clinical AI feature
- Network isolation and VPC configuration
- SOC 2 Type II and HITRUST audit-ready documentation
- Drift monitoring and model versioning
- Incident response runbook
- Quarterly security review for ongoing engagements
Why on-prem LLM hosting matters
Use case 1 · Data sovereignty
Federal, VA, and defense health contracts often require PHI never leave your network. On-prem LLM is the only path.
Use case 2 · Cost predictability
At high inference volume, on-prem LLM costs less than per-token API pricing. Break-even is typically 10M+ tokens/month.
Use case 3 · Latency-sensitive workflows
Sub-200ms response time for clinical copilots and ambient documentation requires inference closer to the EHR. On-prem wins on latency.
Use case 4 · Fine-tuning on PHI
Fine-tuning on PHI requires the training data to stay inside your compliance perimeter. Open-weight models deployed on-prem make this possible without third-party exposure.
Use case 5 · Audit and regulatory scrutiny
Some regulators and payers want documented control over the model itself, not just the API. On-prem provides that audit story.
8-week HIPAA-compliant cloud buildout timeline
01
Weeks 1–2 · Assessment + design
Current-state audit, BAA paperwork started, target architecture design, compliance gap analysis.
02
Weeks 3–4 · Infrastructure buildout
HIPAA-compliant cloud deployment (AWS/Azure/GCP), network isolation, encryption, IAM setup, audit logging plumbed.
03
Weeks 5–6 · AI integration
BAA-covered AI provider connection, zero-data-retention configuration verified, override-and-audit UX, model versioning.
04
Weeks 7–8 · Validation + handover
Security review, penetration testing, SOC 2 documentation, runbook handover, team training.
Ship AI on PHI without breaking HIPAA
Free 30-min architecture call. We’ll review your AI use case, your data residency requirements, and the right deployment path — cloud, on-prem, or hybrid.
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FAQs
FAQ
Six things: signed BAA with every AI provider in the inference path, encryption at rest and in transit, zero-data-retention configuration, audit logging on every model output, role-based access control, and override-and-audit UX on clinical AI features. Missing any one of these is a HIPAA exposure.
Yes — all four sign BAAs for healthcare customers. Each has specific configuration requirements (zero data retention, designated endpoints, enterprise tier) to be BAA-eligible. Taction has pre-signed BAA templates with all four providers and active BAA paper trails on shipped engagements.
Four scenarios: (1) data sovereignty requirements like federal or VA contracts where PHI cannot leave your network, (2) high inference volume where on-prem becomes cheaper than per-token pricing (typically 10M+ tokens/month), (3) latency-sensitive workflows under 200ms response time, (4) fine-tuning on PHI where the training data must stay inside your compliance perimeter.
From $130K for a deployment-only engagement (open-weight model deployed in your data center or VPC, inference API, audit logging, monitoring). From $220K with institution-specific fine-tuning. Hardware costs are separate — typical GPU server configurations run $50K–$200K depending on model size and concurrency.
A productized 4-week audit of your current AI infrastructure. We review BAA paper trails, inference endpoints, audit logging, access controls, and override-and-audit UX. Output is a written gap analysis, prioritized remediation roadmap, and executive summary. Counts as Discovery Sprint credit if you proceed to a compliant cloud buildout or on-prem deployment.
Yes. Every Taction healthcare engagement is BAA-covered from day 1. We sign BAAs on the engineering services contract, and our deployments include pre-signed BAA templates between you and every AI provider in the inference path.
Yes. Audit logging, access controls, encryption, and incident response runbooks are designed to meet SOC 2 Type II and HITRUST CSF requirements. We provide the documentation auditors expect; we don’t conduct the audit itself (third-party auditors handle that).