Unified Data Platform
The Challenge
The client — an FTSE-100 healthcare leader — had data scattered across 5+ siloed warehouses, each with different security models, access controls, and governance standards. This fragmentation made enterprise-wide analytics nearly impossible and completely blocked any AI initiatives that required cross-domain data access. There was no unified security posture, no consistent governance, and no foundation for the AI applications leadership wanted to build.
Solution & Approach
We led the security architecture for a complete data platform re-platforming — consolidating all silos into a unified platform on AWS and Snowflake. Every security policy was implemented as code using Terraform: customized IAM roles, KMS encryption, and resource-level policies that enforce governance automatically. We engineered secure integration pathways between AWS and external systems (Azure, Salesforce, Snowflake, on-premise environments), ensuring data could flow safely across boundaries. This platform became the foundation for all four AI applications we subsequently built for this client.
- Security as code — All IAM, KMS, and resource policies defined in Terraform, ensuring consistent governance across all environments.
- Multi-cloud integration — Secure data flows engineered between AWS, Azure, Salesforce, Snowflake, and on-premise systems.
- AI-ready architecture — The unified platform directly enabled the NL-to-SQL assistant, legal document agent, sales chatbot, and automated case resolution systems.
- Pipeline automation — Automated creation and updating of all cloud resources via CI/CD pipelines using Step Functions and Lambda.
Results & Impact
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