From on-prem legacy to an AI-driven cloud platform
We led the migration of an enterprise software vendor's legacy on-premise product to a modern, cloud-native platform with AI capabilities — modernising the architecture while keeping the business running throughout.
The challenge
A large on-prem monolith was expensive to run, slow to release, and hard to scale. Customers wanted modern, AI-powered features the existing architecture simply couldn't support — and a "big bang" rewrite was far too risky for a product in active use.
Our approach
We used a strangler-fig strategy: incrementally carving capabilities out of the monolith into independently deployable services, moving them to the cloud, and routing traffic across without downtime. New AI/ML services were added on the modern platform as it grew.
- Incremental decomposition of the monolith into containerised, independently deployable services.
- Migration to AWS on Kubernetes, with infrastructure-as-code (Terraform) and blue/green deploys.
- Re-architected data layer and event streaming to decouple services and improve scalability.
- New AI/ML services powering the product features customers had been asking for.
- Observability and automated rollback to de-risk every step of the migration.
Before / after
Technologies used
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