Building the Intelligence Layer for Renewable Energy's Future
Kadhirvel
CTO
TruBoard Cleantech
Building the Intelligence Layer for Renewable Energy's Future
Kadhirvel
CTO
TruBoard Cleantech
“The best way to predict the future is to invent it.” — Alan Kay
Kadhirvel has spent his career bringing this philosophy to life. Over nearly two decades, he has worked across diverse technology domains right from mobile applications and e-commerce to fintech, cloud platforms to renewable energy, building solutions that address complex challenges and create measurable business value.
His journey began in a classroom, teaching programming, databases, and operating systems. Those early experiences instilled a problem-solving mindset that continues to shape his leadership today: understand systems deeply, simplify complexity, and build technology with purpose. As industries evolved, so did his career, taking him through a series of engineering and leadership roles before becoming chief technology officer at TruBoard Cleantech.
Today, he is focused on helping solve one of renewable energy’s most pressing challenges: turning fragmented data into actionable intelligence. Speaking with TradeFlock, Kadhirvel highlighted the growing role of data-driven decision-making in improving asset performance, reducing operational inefficiencies, and enabling a smarter, more sustainable future for renewable energy.
How are you leveraging AI, cloud technologies, and analytics to enhance renewable energy operations?
At TruBoard Cleantech, our flagship platform, TruGreen, acts as the intelligence layer for renewable energy asset management. Built on a cloud-native architecture, it enables real-time data integration from solar, wind, and battery energy storage assets, providing a unified view of performance. Advanced analytics help identify generation losses, separate controllable factors from uncontrollable ones, and deliver actionable insights to operators.
AI takes this a step further by enabling predictive intelligence, helping detect underperformance before it affects output. For Independent Power Producers (IPPs), this translates into improved asset utilisation, greater operational efficiency, and faster, data-driven decision-making across their renewable energy portfolios.
How do you balance AI innovation with reliability, governance, and long-term value?
I am a strong believer in disciplined architecture. While AI offers tremendous opportunities, the systems we support in renewable energy are mission-critical, making reliability non-negotiable. My approach is to encourage innovation in controlled environments, validate outcomes rigorously, and only then deploy solutions at scale. At TruBoard,
I recently led the development of an enterprise AI governance framework to bring structure to the growing adoption of AI tools across teams. The objective was not to restrict innovation but to ensure it remains secure, aligned with business goals, and capable of delivering long-term value. Governance enables responsible scale, keeping automation and AI both effective and dependable.
What leadership values have remained constant throughout your career, and how do you inspire innovation within your engineering teams?
Across every technology domain I have worked in, two principles have remained constant: ownership and clarity. I want engineers to feel accountable for outcomes, not just the code they write. At the same time, I believe that if a solution cannot be explained simply, it is not understood well enough.
To encourage innovation, I give teams the freedom to experiment while maintaining strong engineering fundamentals and disciplined execution. Continuous learning is essential in a field that evolves so rapidly. I also believe in leading by example, staying involved in architecture and prototyping to foster a culture built on curiosity, accountability, and continuous improvement.
What have been the most complex technology challenges you've faced in renewable energy, and how have you addressed them?
One of the biggest challenges in renewable energy is managing fragmented data. Information comes from multiple OEMs, SCADA systems, and wind turbine vendors, each with its own formats and standards. Building a unified data model across more than 230 turbines and multiple sites required significant engineering effort. The larger challenge was connecting technical performance, plant operations, commercial metrics, DSM obligations, and energy trading data into a single, meaningful view.
To address this, we developed a robust data ingestion and normalisation framework and adopted physics-informed AI to reflect actual asset behaviour. Bringing together engineering, physics, and domain expertise was key to making it work.
How do you see Agentic AI transforming renewable energy over the next five years?
I am very keen on Agentic AI. Today, our platforms tell you what is happening and why. In the next five years, agentic systems will start to act, raising work orders, scheduling maintenance, and coordinating across O&M teams with minimal human effort.
For renewable energy, the biggest opportunity is autonomous O&M: an agent that detects a fault, diagnoses it against asset history, and triggers the right action automatically. The second big area is commercial including agents handling invoicing, receivables, and reporting workflows. The human role shifts to supervision and judgement, while the routine, repetitive work is handled by agents.
What is your vision for TruBoard's role in accelerating sustainable energy adoption?
My long-term vision is for TruBoard to become the intelligence layer for renewable energy operations, not merely a monitoring platform, but a system that actively helps operators run clean energy assets more efficiently. I want our technology to serve as a trusted single source of truth for asset performance across the industry.
Beyond technology, the larger goal is to contribute meaningfully to the global energy transition. Every generation loss avoided and every hour of downtime prevented improves the economics of renewable energy. If our platforms help independent power producers optimise performance and invest confidently in additional renewable capacity, we will have made a meaningful impact.
