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Enterprise software

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

Infrastructure cost
Before — baseline
After — −40%
Platform uptime
Before — variable
After — 99.9%
Release frequency
Before — quarterly
After — 3× more often

Technologies used

AWSKubernetesTerraformDockerPythonPostgreSQLApache Kafka

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