Reinvent data centres for the AI-driven, green future: Anil Nama, CtrlS

How is CtrlS using AI to optimise energy, cooling, workload distribution, and minimise downtime through predictive maintenance? Any recent standout innovations?

At CtrlS Datacenters, we leverage AI to optimise critical datacenter functions, ensuring peak performance and reliability for AI-driven workloads. Our AI-ready infrastructure is designed for HPC, AI, ML, and LLM, supporting data analytics, deep learning, and data mining. State-of-the-art cooling systems, like immersion cooling and precision air conditioning, coupled with high-density power solutions, manage intensive AI workloads efficiently and sustainably. Furthermore, a robust network infrastructure with low-latency connectivity ensures seamless handling of massive data requirements for AI training and inference, contributing to minimised downtime and improved uptime.

Our AI-optimised facility design, with a modular, scalable approach and low PUE (Power Usage Effectiveness), further supports workload distribution and operational efficiency. CtrlS’ AI-ready network infrastructure offers multiple ISP and IX connectivity options to maintain minimal latency, which is crucial for AI inference and training. With a commitment to 100% renewable energy by 2030 and major sustainability awards, we are setting new standards in energy management and sustainable AI-ready datacenter operations.

How is AI enabling CtrlS to support emerging technologies like 5G, IoT, edge computing, and hybrid cloud environments more effectively?

At CtrlS Datacenters, we leverage a combination of predictive analytics, machine learning, and automation AI to optimise critical functions and support emerging technologies. For 5G and IoT, our AI-powered infrastructure uses machine learning algorithms to handle massive data volumes, delivering real-time insights and enabling low-latency applications through our robust, low-latency network. In edge computing, predictive analytics optimises node placement and workload management across distributed locations. For hybrid cloud, automation AI facilitates seamless integration and resource management, optimising workload placement and automating provisioning, all within a secure and compliant framework. This is all underpinned by our AI-ready infrastructure, designed for high-performance computing and intensive AI workloads, managed sustainably with advanced cooling and power solutions.

Furthermore, our $2 billion investment plan aims to add 350 MW of AI and cloud-ready hyperscale data centres, incorporating advanced technologies such as liquid cooling and AI-optimised rack layouts to meet the growing demands of 5G, IoT, and hybrid cloud environments.

How do you envision the ‘data centre of the future’? What role will AI play in its design, sustainability, and resilience?

We envision the future datacenter as a dynamic, intelligent ecosystem with AI at its core. In design, AI will optimise layouts, cooling strategies, and predict capacity needs. For sustainability, AI will drive energy efficiency, optimise water usage, and enable renewable energy integration, transforming data centres into active participants in a sustainable energy grid. In resilience, AI will provide proactive threat detection, automated failover, and self-healing infrastructure, ensuring continuous operation despite disruptions. Essentially, AI will transform data centres from static infrastructure into dynamic, intelligent ecosystems.

This transformation is already underway across the industry, responding to significant challenges ahead. According to a report from the International Energy Agency, data centres currently consume about 1-1.5% of global electricity, with projections indicating this demand could nearly double to 1,000 terawatt-hours annually by 2030, equivalent to Japan's entire electricity consumption, primarily driven by the explosive growth of AI applications. To address this, advanced cooling technologies like liquid cooling and heat recycling are now being utilised to minimise the 40% of energy generally allocated for cooling operations. Additionally, AI enables smarter integration of renewable energy sources through real-time grid condition monitoring and usage pattern optimisation. These developments collectively facilitate the establishment of robust and sustainable infrastructure necessary for future AI applications and reduce environmental impact.

Any specific innovations or expansions CtrlS is planning in the next 12–18 months around AI-powered infrastructure?

CtrlS has allocated INR 500 crore for a new AI-ready datacenter in Bhopal, equipped with advanced cooling and security systems designed for optimal performance with AI and cloud workloads. This centre is projected to create approximately 200 jobs. A significant MoU with the Telangana government, signed at Davos 2025, will initiate the development of a ₹10,000 crore, 400 MW AI-enabled datacenter cluster near Hyderabad, expected to generate 3,600 jobs and enhance India’s AI ecosystem. CtrlS is also commencing work on a 40-acre AI-ready datacenter park at Chandanvelly Industrial Park, featuring phase-1 power of 250 MW and adaptable ultra-high-density rack configurations supporting up to 135 KW per rack alongside liquid immersion cooling capable of 300 KW per rack. We are also extending AI-ready infrastructure to tier-2 markets such as GIFT City (Ahmedabad), Bhubaneswar and Guwahati, bringing localised, low-latency compute and storage closer to emerging enterprise and IoT hubs. These developments are part of CtrlS’ larger $2 billion investment plan to increase AI-optimised hyperscale and edge capacity by 350 MW across India and selected Southeast Asian regions.

How do you see the role of traditional enterprise data centres versus the rise of hyperscale and colocation models in today's ecosystem?

Each model has its place. Hyperscale data centres are ideal for large-scale, standardised workloads. Colocation data centres offer flexibility and scalability for organisations that want to outsource their infrastructure management. Traditional enterprise data centres still have a role for organisations with specific security, compliance, or latency requirements. We are seeing a trend towards hybrid solutions, where organisations combine these models to meet their diverse needs. An estimated 10 GW of new hyperscale and colocation capacity will break ground globally in 2025, with an additional 7 GW completing, underscoring record-high investment in flexible, scalable infrastructure that underpins hybrid and multi-cloud strategies. CtrlS is well-positioned to support this trend, offering a range of colocation and managed services that can be tailored to specific requirements. This hybrid approach allows organisations to leverage the cost efficiencies and scalability of hyperscale facilities while maintaining critical workloads in enterprise or colocation environments that offer greater control and customisation. Factors driving these decisions include data sovereignty requirements, application performance needs, and total cost of ownership considerations. The evolution toward distributed digital infrastructure also supports emerging edge computing demands, with IDC forecasting that 50% of new enterprise IT infrastructure will be deployed at the edge by 2026.

There’s increasing momentum around small and edge data centres, especially with the growth of IoT and low-latency applications. What is CtrlS’s strategy in this space?

We recognise the growing importance of edge computing. Our strategy is to partner with key players in the edge ecosystem to provide comprehensive solutions. This includes offering colocation services in strategic locations, as well as developing managed services that can be deployed at the edge. We are also exploring strategic investments in edge infrastructure to expand our reach and capabilities.

CtrlS currently operates edge data centres in Patna and Lucknow, which are engineered for low-latency and high-performance workloads. Further expansions are slated for GIFT City (Ahmedabad), Bhubaneswar, and Guwahati, reflecting a strategic push into tier-2 markets to meet growing enterprise demand for localised infrastructure. This growth trajectory is in step with broader industry trends: IDC’s Worldwide Edge Spending Guide estimates global spending on edge computing at $228 billion in 2024, with a forecasted rise to $378 billion by 2028, demonstrating a sustained double-digit CAGR that underscores the sector’s momentum. We plan to establish over 20 Edge data centres across Tier-II and Tier-III locations. These edge deployments are critical for supporting next-generation applications requiring sub-millisecond latency, particularly in manufacturing, healthcare, and smart cities.

What are some unique challenges and opportunities when it comes to managing smaller or edge data centres, especially in remote or tier-2 locations?

Managing edge data centres, particularly in Tier 2 locations like Patna, Kolkata, and Lucknow, presents unique challenges. The heterogeneity of environments and use cases across sites, ranging from manufacturing plants to retail outlets, adds complexity to standardised operations. Limited local technical expertise and a lack of trained staff necessitate secure, automated remote management tools to maintain visibility and control without frequent site visits. Security is paramount, given the increased vulnerability to physical and cyber threats. Power and cooling can also be challenging, demanding innovative solutions. However, we see significant opportunities in these markets.

Despite these challenges, our Tier 2 expansion enhances our ability to deliver low-latency, edge-computing solutions to regional businesses and users, enabling new applications and services. This strategic move leverages untapped markets and supports growing digital demands, offering a competitive advantage. Furthermore, edge data centres improve the resilience of critical infrastructure by providing backup and failover capabilities. By partnering with telecom providers and local training institutions, operators can create a skilled workforce to support these sites and scale networks efficiently. As we expand our edge footprint beyond Patna, Lucknow, Ahmedabad, Bhubaneswar, and Guwahati, we are committed to addressing these challenges and capitalising on the opportunities to support the growth of local businesses and communities.

How has CtrlS integrated sustainability into its design and operations philosophy? Could you elaborate on the technologies and frameworks you’re using to make data centres more eco-friendly?

Sustainability is central to CtrlS's design and operations philosophy. We are focused on achieving low Power Usage Effectiveness (PUE) through advanced cooling techniques and energy-efficient designs. To meet digital service demands, we implement liquid cooling systems for high-density servers, using coolants to directly dissipate heat more effectively than traditional air cooling. We've also introduced adiabatic cooling, leveraging water evaporation for natural cooling. To optimise further, proactive microclimate analysis and Computational Fluid Dynamics (CFD) predict and manage airflow and temperature variations with precision. By striving for industry-leading PUE metrics, we aim to reduce energy usage and cooling costs, enhancing both operational efficiency and sustainability.

Over the past year, CtrlS has commissioned Phase I (50 MW) of its 100 MW GreenVolt 1 captive solar farm in Nagpur, Maharashtra. Phase II, adding another 50 MW is underway. In Noida, our DC1 facility now meets 60% of its annual power needs from solar, and our Chennai Datacenter Campus has recently achieved LEED Platinum certification, underscoring our commitment to sustainable and energy-efficient operations. Looking ahead, we are committed to achieving Net Zero by 2040 with a roadmap that includes investing in 1,000 MW of variable renewable energy and battery storage, deploying variable-frequency drives on HVAC equipment, phasing out single-use plastics, and installing EV charging stations for a circular economy ecosystem.

As AI, quantum computing, and decentralisation become more prevalent, how is CtrlS planning for the data centre of the future? 

CtrlS is preparing for AI, quantum computing, and decentralisation by strategically embracing edge computing. This brings computational power closer to data sources, reducing latency and enabling real-time processing within our hybrid cloud framework. This supports faster decision-making across sectors like telecom and healthcare. Our edge datacenters, located near critical applications, host 5G ecosystems, support high-bandwidth deployments and address data sovereignty concerns.