Cloud AI Modernisation for Healthcare
Migrate legacy healthcare AI from experimental notebooks to production-grade cloud platforms. HIPAA-compliant RAG pipelines, MLOps, and observability for clinical AI at scale.
Healthcare & Life Sciences Challenges
HIPAA compliance and patient data protection
Integration with legacy EHR systems
Clinical validation and regulatory approval
Bias detection in medical AI models
Real-time inference for critical care
How Cloud AI Modernisation Solves Healthcare & Life Sciences Challenges
Refactoring AWS, Azure, GCP, and Oracle workloads into production-grade AI stacks. Multi-cloud RAG pipelines, observability, guardrails, and MLOps that slot into existing engineering rhythms.
Multi-Cloud RAG Pipelines
Production-ready retrieval augmented generation across AWS, Azure, GCP, and Oracle with unified governance.
MLOps Integration
CI/CD pipelines, model versioning, A/B testing, and automated deployment workflows integrated with existing DevOps.
Observability Stack
Real-time monitoring, alerting, cost tracking, and performance dashboards for AI workloads.
Production Guardrails
Content filtering, toxicity detection, PII redaction, and rate limiting to keep AI safe in production.
Use Cases
- ✓Production RAG pipelines for clinical knowledge bases
- ✓MLOps for medical imaging model deployment
- ✓Multi-cloud clinical decision support systems
- ✓HIPAA-compliant AI observability and monitoring
- ✓Scaling pilot clinical AI to enterprise deployment
Key Benefits
HIPAA-compliant cloud AI infrastructure
Faster deployment of clinical AI models
Unified governance across cloud providers
Cost-optimized inference for healthcare workloads
Enterprise-grade monitoring and guardrails
Technology Stack
Ready to Deploy Cloud AI Modernisation for Healthcare & Life Sciences?
Let's discuss how our cloud ai modernisation capabilities can address your healthcare & life sciences challenges.
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