SofStack is a healthcare AI MVP development company building AI products for hospitals, clinics, healthtech companies and life sciences teams.
Healthcare AI has a higher bar than most industries. It must protect patient data, fit clinical workflows and support, not replace, clinical judgement. We build healthcare AI MVPs with privacy, safety and human oversight designed in from the start.
Who We Build Healthcare AI For
Hospitals and health systems reducing administrative load on clinical staff
Clinics and care providers improving patient communication and scheduling
Healthtech companies adding AI features to their platforms
Digital health startups with funding launching AI-first products
Pharma and life sciences teams working with research and trial data
Health insurers and TPAs automating claims and prior authorisation work
Healthcare AI MVP Use Cases
Clinical Documentation Assistants
AI that drafts visit notes, discharge summaries and referral letters from clinician input, ready for review and sign-off.
Patient Intake and Triage Support
Conversational intake that collects symptoms and history, then routes patients to the right service with clinician oversight.
Medical Document Processing
Extraction of data from lab reports, referrals, insurance forms and scanned records into structured fields.
Revenue Cycle Automation
Coding suggestions, claim checks, denial analysis and prior authorisation document preparation.
Patient Communication Assistants
Appointment reminders, pre-visit instructions and answers to common questions in plain language.
Research and Clinical Data Analysis
Literature summarisation, cohort analysis and trial document review for research teams.
Patient Data Privacy and Compliance
We design healthcare AI around the privacy rules that apply to your market, including HIPAA in the US, UK GDPR and GDPR in Europe, and India's DPDP Act.
HIPAA-aware architecture with PHI identified, minimised and protected
De-identification of patient data in development and testing
Encryption of data in transit and at rest
Role-based access and audit logs of every access to patient data
Your cloud environment: deployment on your HIPAA-eligible AWS, Azure or Google Cloud services
Model choice for PHI: enterprise LLM endpoints or self-hosted models so patient data is not retained by third parties
Clinical Safety by Design
Clinician in the loop: AI outputs are drafts or suggestions, reviewed by qualified staff
Clear scope: the MVP is designed as decision support, not diagnosis
Source grounding: answers reference the records or guidelines they come from
Clinical evaluation sets reviewed by your medical experts before launch
Bias checks across patient groups where outputs could affect care
Healthcare System Integrations
System | Integration approach |
EHR / EMR platforms | FHIR and HL7 APIs, vendor app frameworks where available |
Practice management | Scheduling and patient record APIs |
Lab and imaging systems | HL7 messages, DICOM metadata and report feeds |
Billing and claims | Claims data, coding systems such as ICD-10 and CPT |
Patient channels | Patient portals, SMS, WhatsApp and web chat |
How We Deliver Healthcare AI MVPs
1. Clinical workflow discovery: we map the workflow with clinicians, admin staff and IT.
2. Privacy and risk assessment: we identify PHI, regulatory needs and clinical risk points.
3. Proof of concept on de-identified data to confirm accuracy and value.
4. MVP build with integrations, access controls, audit logging and clinician review steps.
5. Clinical validation: testing with your medical experts on real-world cases.
6. Controlled rollout to a single department or site before wider launch.
Healthcare AI MVP Pricing
Engagement | Starting price | Timeline |
Healthcare AI Discovery | From $2,500 | 2 weeks |
Proof of Concept | From $5,000 | 3–4 weeks |
Healthcare AI MVP | From $20,000 | 10–14 weeks |
Dedicated Healthcare AI Team | From $6,000/month | Monthly |
Healthcare projects include additional privacy, security and validation work, reflected in the MVP pricing.
Frequently Asked Questions
Can you build HIPAA-aware AI applications?
Yes. We design for PHI protection with de-identification, encryption, access controls, audit logs and deployment on HIPAA-eligible cloud services in your account.
Do you build AI that diagnoses patients?
Our healthcare MVPs focus on decision support and administrative automation, with clinicians reviewing outputs. Diagnostic medical devices require regulatory clearance, which we can plan for with your regulatory team.
Can your AI connect to our EHR?
Yes, where the EHR provides APIs. We use FHIR and HL7 standards and vendor integration frameworks.
How long does a healthcare AI MVP take?
Most healthcare AI MVPs take 10 to 14 weeks, including privacy review and clinical validation. A POC on de-identified data takes 3 to 4 weeks.
How much does healthcare AI development cost?
SofStack healthcare AI MVPs start from $20,000, with proofs of concept from $5,000.
Will patient data be sent to public AI models?
No. We use enterprise endpoints with no data retention or self-hosted models inside your environment, and de-identify data wherever possible.
Start Your Healthcare AI MVP
Tell us about the workflow you want to improve. We will outline a privacy-first approach and the right starting engagement.