DeepCoolAI | Data Center Cooling Solutions Company Of The Year 2025
DeepCoolAI: Building the Next Generation of AI Factories with Liquid Cooling Power
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CIOREVIEW >> Datacenter >> DeepCoolAI

DeepCoolAI has been recognized by CIOReview Magazine as the recipient of “Data Center Cooling Solutions Company Of The Year 2025,” based on our proprietary methodology, reflecting its position in the industry. This profile has been developed by the CIOReview research and editorial team based on insights from an interview with Kris Holla, CEO and Founder.

DeepCoolAI
Building the Next Generation of AI Factories with Liquid Cooling Power

DeepCoolAI

Kris Holla, CEO and Founder
Modern data centers have become sprawling AI factories, powering workloads for hyperscalers and co-location operators at unprecedented scale. Running advanced AI models requires dense clusters of high-powered GPUs that generate far more heat than traditional servers. Conventional air cooling cannot keep up. Operators must validate thermal performance, commission infrastructure, and prepare systems well before multi-million-dollar GPU servers arrive. Any delay directly affects uptime and revenue, making speed and reliability critical.

Meeting these demands involves multiple phases. During design, teams plan liquid-cooled layouts for dense GPU clusters. Startup and commissioning require validating thermal loads, electrical circuits, and liquid loops at megawatt scale, all while avoiding leaks, debris, and chemical imbalances. Once live, ongoing operations depend on safe methods for filling, testing, and maintaining racks, as well as tools to manage fluids and cooling distribution efficiently. The scale and complexity leave operators seeking specialized solutions that deliver speed, safety and repeatable results.

DeepCoolAI addresses these challenges with a full-stack ecosystem of liquid-cooling infrastructure and commissioning tools designed for AI-scale Factories. The company provides everything from CDUs, hybrid load banks, refill carts, and manifolds to RDHx, fanwalls, and validation systems—creating a seamless bridge from design to operation. This integrated suite enables hyperscalers and cloud providers to accelerate deployment, simplify commissioning, reduce operational risk, and sustain efficient, reliable performance across their liquid-cooled data centers. These solutions ensure facilities operate safely and efficiently at the speed and scale demanded by the rapidly expanding AI economy.

End-to-End Design and Startup Tools Enabling Faster, Safer GPU Deployments

DeepCoolAI’s mission is to turn data centers into true AI factories, where thermal reliability and speed of deployment translate directly into business value. Each phase of a project requires specialized equipment, and DeepCoolAI supports customers across three critical stages.

The first stage involves designing liquid-cooled data centers, where layouts, loops, and thermal strategies must be set long before construction begins. The second stage begins when a new building reaches the startup and commissioning phase. Operators must validate thermal loads, technical loops, and electrical performance before bringing in GPU servers that can cost more than three and a half million dollars each from vendors such as Nvidia, Supermicro, or Dell. The third stage focuses on ongoing maintenance and operations, where fluid management and service tools keep every rack running within tight chemical and mechanical tolerances.

The product range reflects that focus on practical solutions. A hybrid load bank is a signature innovation because it can simulate both air and liquid loads in one platform, allowing engineers to test thermal and electrical performance before expensive equipment is installed. A 1.4-megawatt liquid-cooled load bank extends this capability further and has been shown to cut commissioning time roughly in half compared with multiple smaller units. Refill carts give technicians a safe and efficient way to fill multiple racks at once while checking pH and conductivity in real time. Flushing kits help clean and maintain coolant loops to prevent contamination for safe operation.

Cooling distribution units, including modular DX versions, extend liquid cooling to sites that lack chilled water access. Prefabricated pods and skids arrive fully wired and plumbed, turning months of on-site construction into a few weeks of installation. Each product addresses a specific obstacle that hyperscalers face when scaling liquid cooling quickly.

Customers include major cloud and Neo Cloud along with leading colocation providers. These organizations measure deployment speed in gigawatts of computing capacity, so every product that removes an obstacle delivers immediate financial impact.

A recent project illustrates how these tools change outcomes. A large hyperscaler asked DeepCoolAI for hundreds of load banks to support an AI expansion scheduled for October. Traditional timelines would have pushed delivery well beyond the target date. Engineers at DeepCoolAI redesigned system elements and shipped the full order by late September, weeks before the deadline. The accelerated schedule allowed the customer to stay on track for GPU deployment and validated the company’s ability to meet urgent demand.

Liquid Cooling Transitions to Large-Scale AI Buildouts

Such results matter because the industry is moving from isolated pilots to full-scale liquid-cooled facilities. High-density GPU clusters require thermal solutions that go far beyond legacy air handling. Operators must commission systems that sustain continuous megawatt loads while maintaining water chemistry and mechanical integrity. Prefabricated pods allow hyperscalers to build AI-ready capacity at a pace that matches market demand. Rental programs extend flexibility by allowing customers to use load banks and refill equipment only when needed, which is an attractive option for colocation providers operating on thin margins.

DeepCoolAI’s story underscores how infrastructure innovation enables the broader AI revolution. Hyperscalers cannot deliver new services or train ever-larger models without cooling systems that keep pace with rising thermal loads. Tools that speed commissioning, simplify maintenance, and reduce on-site complexity allow operators to focus on scaling compute power rather than managing risk. Each product, from CDUs, and hybrid load bank to the mobile refill cart, exists to remove a specific obstacle for customers who cannot afford downtime.

Advanced Technology and Global Capacity Paving the Way for Scalable AI Growth

Data center operators already measure buildouts in gigawatts, and the move to liquid cooling will only accelerate. DeepCoolAI positions itself as a partner that understands the urgency of this moment and provides the hardware, service, and manufacturing depth required to meet it. Combining innovative products, rapid execution, and strategic partnerships gives customers a path to scale AI infrastructure without sacrificing reliability or speed.

The company has co-developed the Oracle Liquid-to-Air Rack Cooling (LARC) solution in partnership with Oracle. Purpose-built to support NVIDIA’s full line of liquid-cooled GPU servers, including the upcoming Blackwell generation, this modular system scales with rack power requirements up to 1 MW—enabling future-ready, high-density deployments. These collaborations reflect DeepCoolAI’s commitment to advancing the ecosystem while ensuring customers can scale rapidly and reliably.

DeepCoolAI has partnered with Sanmina Corporation for global manufacturing, logistics, and supply chain execution at scale. This partnership enables DeepCoolAI to deliver its innovative solutions with consistent quality, speed, and reach across North America, EMEA, and APAC—supporting hyperscalers and colocation providers with dependable global supply chain capacity.

DeepCoolAI has announced its merger with MAS HVAC, creating one of the industry’s most comprehensive and scalable thermal management platforms. By combining DeepCoolAIs leadership in liquid cooling and hybrid load-bank technologies with MAS HVACs Daedex® branded precision air cooling capabilities, the integrated platform can now deliver fully unified, end-to-end thermal management solutions for hyperscale, colocation, and enterprise data centers. Through the outsourcing partnership between Sanmina, DeepCoolAI has delivered Hybrid Load Banks in high volumes with exceptional speed by leveraging Sanminas advanced Fremont manufacturing capabilities. It ensures consistent quality, rapid scalability, and global reach.

The company holds several pending patent for its Hybrid Cooling Load Banks, CDUs and pre-fabricated solutions underscoring its commitment to technology leadership and continuous innovation.

Servers may run software models that capture the world’s attention, but those models depend on pumps, pipes and coolant loops that must work flawlessly. DeepCoolAI provides the equipment and expertise that make those loops possible. The success of its early deployments demonstrates that the right tools can turn a cooling challenge into a competitive advantage, giving data centers the confidence to build the AI future at full speed.

Data Center Cooling Solutions Company Of The Year 2025

Company
DeepCoolAI

Headquarters
.

Management
Kris Holla, CEO and Founder

Description
DeepCoolAI is a One Stop Factory for Direct Liquid Cooling at Next Gen AI Factories. DeepCoolAI offers a comprehensive range of solutions for liquid cooling, including CDUs, Load Banks, Refill Carts, and supporting products such as RDHx and Fanwalls. We specialize in custom-tailored CDUs, providing bespoke solutions for data centers ranging from 1 megawatt to 6 megawatts. Our plug-and-play Load Banks are designed to streamline the commissioning and startup of AI liquid-cooled data centers. Additionally, our state-of-the-art Refill Carts ensure that your liquid-cooled servers and CDUs remain operational, helping you maximize uptime. Recently, Sanmina and DeepCoolAI entered into a strategic partnership for global manufacturing and supply chain at scale.

Data Center Cooling Solutions Company Of The Year 2025

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