MCJ Invests in Hammerhead AI's $10M Seed
Unlocking more compute capacity from existing data-center power limits
Behind every AI boom headline is a quieter bottleneck. Across the world’s major data-center hubs, from Northern Virginia to Dublin to the Pacific Northwest, operators are running into the same foundational constraint: power. New substations take years to permit, new transmission can take nearly a decade, and utilities are increasingly restricting peak consumption just as AI workloads surge.
Yet most data centers operate far below their potential—typically around 40% utilization despite 100% capacity. This isn’t operator error; it’s structural over-provisioning for reliability. To meet “five nines” uptime requirements (operational 99.999% of the time), facilities reserve massive power buffers for rare peak events that might occur just hours per year. Studies like the 2024 Lawrence Berkeley National Laboratory report confirm average utilization sits at 30–50%, meaning nearly half of all provisioned power goes unused.
The inefficiency compounds with AI workloads. Training runs and batch inference are latency-tolerant (they don’t need instantaneous response), yet data centers treat them like mission-critical transactions. Without intelligent orchestration to reshape and shift flexible workloads around peaks, enormous compute capacity sits stranded. Data centers are simultaneously power-constrained and sitting on vast unused capacity they can’t unlock.
This gap between provisioned capacity and actual usage represents one of the most interesting economic opportunities in the entire compute value chain.
Hammerhead AI is turning this hidden capacity into usable compute. Their technology applies the founders’ experience orchestrating gigawatt-scale virtual power plants to AI infrastructure, dynamically coordinating rack-level power, GPU load, cooling, UPS systems, and on-site storage. MCJ is excited to back Hammerhead AI in its $10M Seed led by Buoyant Ventures. Keep reading to see how Hammerhead fits squarely into our new investment theses.
What is Hammerhead AI?
Hammerhead’s software, known as ORCA (Orchestrated RL Control Agents), transforms the data center from a static, over-provisioned asset into a responsive, power-aware system. By reshaping workloads and orchestrating power in real time, Hammerhead enables facilities to generate 20–30% more compute output from the same grid allocation.
Why Did We Invest?
Unlocking the AI Value Chain
We invested in Hammerhead because it sits at one of the most valuable bottlenecks in the AI value chain. Electricity demand is rising faster than supply, and data centers must make every electron more productive. While the market chases new generation or long-duration storage, Hammerhead tackles the problem from the inside out—unlocking more performance from infrastructure operators already have. Instead of delaying deployments or turning away customers, data centers can use their existing power far more intelligently.
The market dynamic strengthens Hammerhead’s position over time. As the industry races to deploy power-hungry GPUs and build new capacity, today’s capital surge may eventually overshoot demand. When that happens, operators will face a second wave of pressure: optimizing operating costs for all this new infrastructure. Power is already the largest line item in data-center P&L. At hundreds of megawatts, even small efficiency gains drive significant margin expansion. Hammerhead becomes a structural OPEX optimizer—extracting more productive compute from each watt. In a world where building capacity is increasingly straightforward but operating it efficiently is not, this platform could be a long-term margin engine.
Founder-Market Fit
What gives us even more confidence is the team behind the technology. Rahul Kar and Rajeev Singh previously were executives at AutoGrid, where they built and scaled industrial control systems overseeing more than 8 GW of orchestrated energy resources before the company’s acquisition by Schneider Electric. Their expertise in mission-critical energy control, industry first cloud NERC-CIP attestation, and large-scale grid integration is exceptionally rare in the AI infrastructure world.
Additional Resources
Solid investment thesis here. The 40% utilization stat really nails the crux of the probem - datacenters are bleeding capacity trying to hit those uptime targets. What's clever about Hammerhead is they're basically applying VPP logic to GPU clusters, which is a way more elegant aproach than just building more infrastructure.