Utthunga has launched a dedicated AI Center of Excellence (CoE) aimed at speeding up the deployment of domain-centric AI solutions across industrial environments. The CoE will develop industry-specific AI models, autonomous engineering agents, and automation tools designed to enhance productivity, shorten engineering cycles, and modernize legacy systems.
The company said the initiative responds to a surge in demand from industrial enterprises that now require secure, scalable, and highly contextual AI systems rather than generic off-the-shelf models. By focusing on real engineering workflows, the CoE will help customers achieve measurable benefits such as 30% productivity improvements, 10% higher asset utilization, and 20% faster delivery timelines, alongside 50% quicker modernization of legacy systems.
To ensure secure deployment, Utthunga has set up private AI infrastructure that allows sensitive customer data to be processed in controlled environments — a growing priority for OT-heavy sectors.
Building Industrial-Grade AI Talent and Infrastructure
The company plans to build a team of 100+ AI specialists by year-end, with more than 50 engineers already trained on agentic AI for industrial use cases. The CoE has also launched an industrial knowledge assistant trained on cross-domain data and is developing an industry-specific Small Language Model (SLM) tailored to manufacturing logic, reliability constraints, and engineering workflows.
Partnerships with universities and AI research startups are being established to strengthen talent pipelines and accelerate R&D. Utthunga said its multidisciplinary teams — covering plant engineering, product engineering, and industrial automation — position it to address the unique constraints of industrial AI deployments.
Solving Industrial Challenges With Domain-Centric AI
“Traditional AI models fall short in complex industrial environments where workflows depend on strict reliability, compliance, and domain-specific logic,” said Dinesh Thukaram, Chief Solutions Officer at Utthunga. He added that the CoE is designed to close this gap by combining engineering expertise with AI technologies that enhance operational efficiency, reduce engineering cycles, and maintain stringent safety standards.
Karthick Ajjan, AI CoE Leader, emphasized that Utthunga is taking a practical, grounded approach to AI adoption. “Our strategy has always been to start with domain-centric use cases. Effective AI outcomes follow only when you design systems around real industrial constraints.”
Driving AI Adoption Across Industrial Functions
Beyond customer deployments, Utthunga is integrating AI into its internal processes — using autonomous agents and automation tools to streamline engineering, documentation, maintenance, and QA workflows. The company aims to use these tested in-house solutions as reusable templates for customers seeking rapid AI adoption with lower risk.
As industries face pressure to deliver intelligent, reliable, and energy-efficient products, Utthunga believes its CoE will play a central role in future-proofing factories and engineering operations.
