Multicloud AI & ERP / Cloud AI Applications & Industry AI Solutions
Why it matters
Clinicians spend hours on documentation, imaging backlogs delay care and patient data is scattered across systems. AI can help with all three, but only on a foundation that meets HIPAA, GDPR and local health regulations.
How it works
The healthcare AI foundation
Clinical systems feed a standards-based FHIR data store with full audit. Data is de-identified before analytics and training. AI models draft notes, read images or flag risks, and a clinician reviews every output that affects care.
AWS, Azure and Google Cloud compared
| AWS | Azure | Google Cloud | |
|---|---|---|---|
| Health data store | AWS HealthLake (FHIR) | Azure Health Data Services (FHIR, DICOM) | Cloud Healthcare API (FHIR, HL7v2, DICOM) |
| Clinical documentation | AWS HealthScribe | Dragon Copilot | Gemini models |
| Medical imaging | AWS HealthImaging | DICOM service | Imaging in Cloud Healthcare API |
| De-identification | Comprehend Medical | De-identification service | Healthcare API de-identification |
| Compliance basis | HIPAA-eligible services, BAA | HIPAA, BAA | HIPAA, BAA |
What makes each cloud different
AWS
AWS offers HealthLake for FHIR data, HealthScribe to draft clinical notes from conversations, HealthImaging for medical images and Comprehend Medical to extract and de-identify clinical text.
Azure
Microsoft's Dragon Copilot brings ambient clinical documentation, Azure Health Data Services stores FHIR and DICOM data and Fabric adds healthcare data solutions for analytics.
Google Cloud
Google's Cloud Healthcare API stores FHIR, HL7v2 and DICOM with built-in de-identification, Healthcare Data Engine builds longitudinal patient records and Gemini models summarize clinical text.
Design decisions that matter
- 01Compliance before AI
BAA, residency and audit first.
- 02FHIR as the data standard
Portable, interoperable data.
- 03De-identify for analytics and training
Minimize identifiable data use.
- 04Clinician in the loop
AI drafts, people decide.
Common mistakes we see
- Pilots on copies of identifiable data. Compliance risk from day one.
- Point solutions per department. Data silos multiply.
- Unvalidated AI outputs in care. Clinical safety and liability issues.
A practical 30-day plan
- Week 1
Confirm BAA, residency and security controls.
- Week 2
Stand up the FHIR store and integrations.
- Week 3
Pilot AI documentation with a clinical team.
- Week 4
Measure time saved and clinician satisfaction.
How NTS helps
NTS builds compliant healthcare AI on AWS, Azure and Google Cloud, covering FHIR data platforms, de-identification, clinical documentation and imaging solutions, with clinicians involved throughout.
What you get
- HIPAA-ready AI architecture
- Clinical documentation and summarization tools
- FHIR integration with health systems
- Privacy and de-identification controls
Typical outcomes
- Less time on clinical documentation
- Patient data protected
- Faster, better-informed care decisions
How we work with you
- 1Assess
A focused review of your healthcare AI across AWS, Azure and Google Cloud. We look for the gaps we find most often: pilots on copies of identifiable data, point solutions per department and unvalidated AI outputs in care.
- 2Design
A target architecture and roadmap built on the decisions that matter most: compliance before AI, FHIR as the data standard, de-identify for analytics and training and clinician in the loop.
- 3Build
Hands-on delivery alongside your team. We confirm BAA, residency and security controls, stand up the FHIR store and integrations, pilot AI documentation with a clinical team, and finally measure time saved and clinician satisfaction.
- 4Run and improve
We monitor accuracy and compliance, and extend AI to new clinical workflows.
Why teams choose NTS for healthcare AI
- Healthcare compliance expertise
We design for HIPAA and patient privacy from the start.
- Clinician-centered
AI reduces paperwork so clinicians can focus on patients.
- Interoperable
We integrate with FHIR and existing health records.
Book a free 30-minute review
Talk to an NTS architect about your healthcare AI on AWS, Azure and Google Cloud.