What problem did you set out to solve when you started DarkNX, and what gap did you see in the data center and AI infrastructure market?
Isaac Islam: DarkNX is a Toronto‑based data center infrastructure company, founded specifically to address the two biggest bottlenecks in next‑generation facilities: power and cooling. Power constraints drive roughly 30% of project cost, while cooling typically represents another 15–20%, so solving these two areas fundamentally reshapes the economics and scalability of AI‑ready infrastructure.
Why DarkNX exists
DarkNX was created to tackle these constraints head‑on, rather than treating them as downstream engineering problems. The model is built around vertical integration and a technology‑agnostic approach, so design, manufacturing, and technology selection are all aligned to future AI workloads instead of today’s minimum requirements.
Principle 1: Vertical integration for power
Vertical integration is how DarkNX attacks the power gap. By bringing key manufacturing and infrastructure delivery in‑house, DarkNX can:
- Move from design to deployment much faster than traditional, fragmented supply chains.
- Design power systems that meet local utility requirements and grid constraints from day one, instead of trying to retrofit late in the process.
Principle 2: Technology‑agnostic cooling
The second gap is cooling architecture, where DarkNX’s technology‑agnostic stance has enabled early adoption of two‑phase liquid cooling at scale. Being one of the first movers on two‑phase solutions means DarkNX can support the highest‑density compute of today while remaining ready for significantly more demanding AI systems tomorrow.
Why this matters vs. traditional models
Traditional players largely rely on single‑phase cooling, which can work for many current workloads but becomes constrained and expensive to upgrade as densities rise. Those environments often need major restructuring to support future AI clusters, adding cost and downtime, whereas DarkNX designs for tomorrow’s requirements from the outset.
DarkNX is focused on next-generation, AI-ready data centers, what makes your approach fundamentally different from traditional data center models?
There are four foundations that guide every DarkNX project:
- Engineered for density: Facilities are designed from day one for high‑density compute, so you get maximum capability without unnecessary overbuilding.
- Liquid‑first thermal stack: Cooling is treated as a unified thermal management system, with liquid cooling as the primary strategy rather than a bolt‑on to traditional air solutions.
- Technology agnostic: The only objective is to create the most cost‑effective compute environment, selecting technologies based on performance and economics, not vendor bias.
- End‑to‑end delivery: DarkNX manages every phase of the project, from design through deployment and operations, providing a single accountable partner throughout the entire journey.
How are you thinking about sustainability, power efficiency, and cooling as AI workloads continue to scale rapidly?
Isaac Islam: DarkNX treats sustainability and efficiency as core power and thermal design problems, not as a PUE optimization exercise. The objective is to keep AI density scaling without a corresponding increase in energy or water consumption.
Our approach centers on liquid-dominated cooling architectures, higher operating temperatures, and high-efficiency mechanical and electrical systems. This reduces total energy demand, enables significantly higher rack densities, and creates viable paths for heat reuse and integration with future low-carbon power sources as AI workloads grow.
When we refer to liquid cooling, we are specifically referring to low-GWP, two-phase refrigerant systems that require no water for heat rejection. Any water usage in our facilities is auxiliary rather than structural, eliminating water as a scaling constraint while improving long-term environmental performance.
Canada is emerging as an important market for AI infrastructure, what opportunities do you see here, and how does DarkNX fit into the global landscape?
Isaac Islam: DarkNX views Canada as one of the most strategically advantaged markets for AI infrastructure globally, and we expect it to become the largest data center market by deployed megawatts by the end of 2027.
Canada’s position is driven by structural advantages: a cold climate that supports free cooling, low seismic risk, robust electrical infrastructure, abundant energy resources, and long-term political stability. These factors materially lower operational risk and improve efficiency at scale, making the country well suited for high-density and hyperscale AI deployments.
Beyond physical infrastructure, Canada’s geopolitical posture and policy orientation favor long-term capital deployment. A stable, diplomacy-first environment enables entrepreneurship, cross-border collaboration, and sustained investment; conditions that accelerate innovation and attract global technology capital.
DarkNX operates at the intersection of these advantages. We design and deliver AI-ready infrastructure that scales efficiently within Canada while remaining fully aligned with global compute demand. Our role is to translate Canada’s structural strengths into deployable, future-proofed data center capacity for the global AI ecosystem.
Looking ahead 3–5 years, what does success look like for DarkNX, and what milestones are you most focused on achieving next?
Success for DarkNX means becoming the largest deployer of AI-ready data center capacity globally, measured by megawatts brought online.
Over the next three to five years, our focus is on scaling repeatable, high-density infrastructure across multiple regions while maintaining speed, cost discipline, and operational consistency. This includes expanding modular deployments, delivering gigawatt-scale clusters, and standardizing power and cooling architectures that can be deployed rapidly without redesign at each site.
The primary milestones are execution-driven: megawatts commissioned, time-to-power reduced, and infrastructure that remains adaptable as AI hardware and power requirements continue to evolve.
Yugbodh (YB) is a contributing writer at Tech Beat Canada, he skillfully weaves captivating stories. For him tech, music and movies serves as an escape, and he finds them fascinating as they constantly evolve. If you have interesting tales to share, feel free to reach out: info@techbeat.ca
