Legacy System Modernization That Enables AI Adoption

We run dual-write patterns during the transition, where new events are written to both the old and new systems simultaneously until the new path has been validated under real production load. Historical migration happens offline, with row count checks, hash verification, and business logic validation against both systems before the legacy path is ever decommissioned. We do not flip a switch. We move traffic incrementally with a rollback path available at each step.

Yes, and this is more common than most AI vendors assume. A number of our clients operate entirely on-premise or in a private cloud, including clients in financial services and healthcare with strict data residency requirements. We modernize the architecture, the API layer, the event bus, and the services without requiring a move to public cloud. AI inference can run on dedicated hardware inside your own data center, and nothing about the approach changes.

Our application modernization services begin with a structured audit of your architecture, codebase, integrations, and infrastructure. This produces a prioritized roadmap showing exactly what is preventing modernization, what should change first, and whether the investment makes financial and technical sense before any engineering begins.

The answer depends significantly on integration complexity rather than the AI logic itself. Systems with clean, documented codebases and modern infrastructure at the edge tend to be less expensive. Systems with deeply embedded business logic, multiple integration points, and compliance constraints that restrict tooling choices cost more. We scope this in detail during the audit phase and give you a fixed estimate before any build work starts. There are no surprises mid-engagement on price.

The strangler fig approach is specifically designed to make this a contained problem rather than a catastrophic one. Each phase introduces new components at the routing layer without touching the code paths the existing system depends on. If anything new behaves unexpectedly, traffic routes back to the legacy path while we investigate. We have run this model across over forty production systems and have not had a production outage during an engagement.