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Kellton Launches Phoenix.AI: Modernizing Enterprise Legacy 80 Percent Faster at Half the Cost

By PNN | Updated: May 18, 2026 14:45 IST

Hyderabad (Telangana) [India], May 18: Kellton Tech Solutions Limited today announced Phoenix.AI, redefining how enterprises modernize legacy systems. Built ...

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Hyderabad (Telangana) [India], May 18: Kellton Tech Solutions Limited today announced Phoenix.AI, redefining how enterprises modernize legacy systems. Built AI-to-the-core and fully scalable by design, the agentic platform re-engineers monolithic estates into cloud-native microservices, compressing multi-year transformation programmes into weeks, accelerating modernization by up to 80%, and reducing costs by up to 50%.

Built on frontier AI capabilities, and orchestrated through Kellton’s proprietary modernization blueprint, Phoenix.AI is already deployed across enterprise engagements, delivering modernization at a velocity and scale previously unattainable through conventional approaches.

Phoenix.AI operates through a continuously running, agentic transformation framework that automates the end-to-end lifecycle of enterprise code modernization — from analysis and decomposition into microservices to conversion, validation, remediation, and quality assurance — while preserving enterprise-grade reliability, governance, and operational continuity.

The platform’s built-in self-correction and execution intelligence further lift engineering productivity, accelerate release cycles, and strengthen transformation outcomes through accumulated delivery learning.

Phoenix.AI is already powering one of the largest AI-led code modernization programmes currently being executed by Kellton, for a US-headquartered global enterprise software leader serving manufacturers across the Americas, EMEA, and APAC.

The engagement involves the migration of more than 4 million lines of source code from Progress ABL/OpenEdge to a modern Microsoft .NET Core and Entity Framework stack, re-engineered into a fully scalable, cloud-native microservices architecture. The programme spans 12 core business modules, including Purchase, Production, Sales, Common Services, and other operational domains forming the backbone of the client’s flagship enterprise platform.

The commercial rollout of Phoenix.AI marks Kellton’s decisive transition from AI experimentation to AI-led enterprise execution at scale, empowering the client to operationalize legacy modernization with unprecedented speed, predictability, and efficiency.

Mr. Niranjan Chintam, Founder and Chairman, Kellton Tech Solutions Limited, said:

“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.”

About Kellton:

Kellton is an AI-led digital transformation and technology consulting company with global delivery capabilities. The company partners with enterprises to build fully scalable digital platforms, modernize legacy estates into cloud-native microservices, and accelerate intelligent automation journeys. With over 2,000 professionals across North America, Europe, the Middle East, and Asia, Kellton delivers solutions across cloud, data, AI, enterprise platforms, and digital product engineering. For more information, visit www.kellton.com.

Disclaimer: This article is for informational purposes only and does not constitute financial advice.

Disclaimer: This post has been auto-published from an agency feed without any modifications to the text and has not been reviewed by an editor

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