Cloud AI Modernisation for Insurance

Modernise insurance AI from legacy systems to production cloud platforms. Multi-cloud infrastructure for underwriting, claims, and fraud detection with enterprise-grade MLOps.

Insurance Challenges

Legacy policy administration systems

Claims processing efficiency

Fraud detection accuracy

Regulatory compliance across states/countries

Actuarial model integration

How Cloud AI Modernisation Solves Insurance 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 underwriting model deployment on cloud
  • Multi-cloud claims processing AI pipelines
  • MLOps for fraud detection model management
  • Real-time policy servicing AI infrastructure
  • Actuarial model migration to cloud compute

Key Benefits

Faster deployment of underwriting and claims models

Unified AI governance across insurance operations

Cost-optimized inference for high-volume processing

Multi-cloud flexibility for insurance workloads

Enterprise-grade monitoring and compliance controls

Technology Stack

Kubernetes / KServeVertex AI & GKEDatabricks MosaicMLMLflow & Feature StoresSnowflake CortexAzure OpenAIAWS BedrockOracle Cloud Infrastructure AI

Ready to Deploy Cloud AI Modernisation for Insurance?

Let's discuss how our cloud ai modernisation capabilities can address your insurance challenges.

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