Kellton launches Phoenix.AI for legacy modernisation

Kellton has launched Phoenix.AI, an agentic AI platform for legacy system modernisation that is already in use in a large code migration programme.

Phoenix.AI is designed to automate much of the process of moving older enterprise software to newer cloud-based architectures. Kellton says it can cut modernisation timelines by up to 80% and reduce costs by up to 50% compared with conventional approaches.

The launch forms part of a broader shift in corporate technology from testing AI tools to deploying them in large operational programmes. Phoenix.AI is designed to handle the full code modernisation cycle, including analysis, decomposition into microservices, conversion, validation, remediation and quality assurance.

The platform has been deployed in a programme for a US-based enterprise software company serving manufacturers across the Americas, EMEA and APAC. Kellton says the project covers the migration of more than 4 million lines of source code from Progress ABL/OpenEdge to Microsoft .NET Core and Entity Framework.

The work also includes re-engineering the software into a cloud-native microservices architecture and spans 12 business modules, including purchase, production, sales and common services.

Large migration

Legacy modernisation has long been one of the costliest and most complex areas of enterprise IT, particularly for companies that rely on monolithic software built over decades. Projects often take years because they require detailed code review, system redesign, testing and efforts to maintain continuity in live operations.

Phoenix.AI uses a continuous agentic framework with built-in self-correction and execution intelligence. Kellton says this approach improves engineering productivity and release cycles by learning from delivery work as programmes progress.

The launch also gives a clearer picture of how Kellton is positioning itself in the market. Operating in North America, Europe, the Middle East and Asia, the company says it has more than 2,000 professionals working across cloud, data, AI, enterprise platforms and digital product engineering.

In comments accompanying the launch, Kellton's leadership pointed to the burden legacy systems place on large organisations. That pressure has become more acute as businesses try to update older systems while controlling costs and limiting operational disruption.

"For decades, enterprise modernization has been a tax on ambition too slow, too expensive, too risky. Deeply embedded legacy estates, rising technology debt, and growing demands for agility have only widened that gap. Phoenix.AI was purpose-built to close it. What sets Kellton apart is that we are not positioning AI as an overlay to transformation; we are embedding it into the core of enterprise engineering and delivery. Phoenix.AI is already accelerating legacy modernization by up to 80%, while cutting transformation complexity, engineering overhead, and associated costs by up to half. Phoenix.AI represents a defining shift in how enterprise transformation will be delivered in the AI era," said Niranjan Chintam, Founder and Chairman, Kellton.

Market shift

The announcement reflects growing interest among technology services providers in using AI agents to carry out more of the work involved in software redevelopment. Rather than limiting AI to coding assistance or testing support, vendors are increasingly presenting these systems as tools that can manage broader workflows across complex engineering programmes.

For customers, the appeal is the potential to shorten projects that can otherwise tie up budgets and technical teams for long periods. Many large organisations still depend on older software stacks that are deeply tied to manufacturing, finance, supply chain and sales operations, making replacement or migration difficult.

Kellton's highlighted customer programme illustrates that challenge in practical terms. A migration involving 4 million lines of code and 12 core business modules would typically rank among the larger and more difficult transformation efforts in enterprise software, especially where operational continuity must be preserved during the transition.

Phoenix.AI is aimed at this part of the market, where companies want to move from legacy environments to cloud-native software structures without running multi-year engineering cycles. Kellton says the platform supports that process by automating code analysis, restructuring and validation while maintaining governance and continuity during the transition.

The commercial rollout marks Kellton's move from AI experimentation to AI-led delivery in enterprise modernisation programmes at scale.