The AI boom has turned GPUs into the most coveted silicon on the planet—yet a surprising portion of them are sitting idle. Not because they lack demand, but because the world’s newly built AI factories (from hyperscalers to colocation giants) can’t feed them enough power. Utilization rates of 30–50% have quietly become the norm. And in today’s AI economics, idle GPUs might as well be burning cash.
Enter Hammerhead AI, emerging from stealth with a $10 million seed round to tackle what may be the most critical—and least glamorous—bottleneck in modern compute: power orchestration. The round was led by Buoyant Ventures, joined by SE Ventures (Schneider Electric’s venture arm), AINA Climate AI Ventures, MCJ Collective, WovenEarth Ventures, Bombellii Ventures, Clearvision Ventures, Stepchange, Acclimate Ventures, and several notable angel investors, including Jack Cogen of CoreWeave.
Hammerhead’s proposition is simple, if not audacious: unlock the stranded power already sitting inside AI factories and convert it directly into token generation. And the company says its platform can boost output by up to 30%—no new substations, no multi-year grid interconnect queues, no new racks.
In a market starved for power, this isn’t just compelling. It’s borderline explosive.
The AI Power Crisis Nobody Wants to Talk About
AI factories—large GPU clusters designed for training, serving, and fine-tuning models—are scaling faster than utility providers can keep up. The shortage has been widely reported, but the more painful truth is that even when operators have power, they’re rarely using it well.
Why?
Because power capacity is allocated to peak usage, but GPUs don’t run at peak 24/7. Cooling loads fluctuate. Grid feeds vary. Workloads aren’t always balanced. Colos may subdivide customer loads conservatively. And hyperscalers operate under rigid safety and redundancy budgets.
The result: megawatts of unused capacity—stranded in plain sight.
Hammerhead claims that in tight markets, each stranded megawatt can be worth $20M–$50M+ in token productivity. That’s a staggering figure, even by hyperscale standards.
Its solution: a software-first real-time control plane that dynamically orchestrates power, cooling, and workload distribution so operators can squeeze every usable watt for productive compute.
ORCA: An RL Engine Built to Maximize Token Production
Hammerhead’s platform goes by the name ORCA—short for Orchestrated RL Control Agents. It’s an autonomous control system that optimizes an AI factory’s token generation per megawatt under operator-defined power constraints.
Unlike traditional data center energy-management software (which mostly focuses on efficiency metrics), ORCA focuses on one KPI above all: token productivity.
ORCA engages across the entire technical stack:
1. Power Infrastructure
- On-site generation
- Battery and storage systems
- Backup and redundancy plans
- Grid feeds and load balancing
2. Non-IT Equipment
- Chillers
- Cooling distribution units
- Pumps and mechanical systems
These often-ignored systems can absorb or release power flexibly—if orchestrated correctly.
3. IT Systems
- Racks
- Servers
- GPUs
- Workload placement and scheduling
4. AI Workloads Themselves
- Sequencing
- Time-shifting
- Model-specific power behavior
All governed by RL agents making real-time decisions in data-dense environments.
If that sounds similar to grid-scale load orchestration, that’s not an accident. Hammerhead’s founders previously built AutoGrid, one of the most successful power orchestration companies in the world, ultimately acquired by Schneider Electric.
This is the same technology playbook—only pointed at AI factories instead of utility-scale distributed energy resources.
“Power is the critical bottleneck in today’s AI landscape, but it doesn’t have to limit what’s possible,” said Rahul Kar, CEO and Founder of Hammerhead. “With ORCA, we’re enabling operators to achieve greater output from existing resources.”
Investors Are Betting Big on Power-Aware AI Infrastructure
The investor list for Hammerhead reads like a who’s who of climate tech, deep tech, data center operations, and AI infrastructure. And that alignment is telling: AI power shortages are increasingly seen as both a climate challenge and a business opportunity.
Some highlights:
- SE Ventures, which backed the founding team’s previous company, sees strategic alignment with Schneider Electric’s data center businesses.
- Buoyant Ventures, the round’s lead, described the team as “the rare combination of deep technical expertise and proven scaling experience.”
- Digital Realty, one of the world’s largest colocation providers, weighed in via VP of Sustainability Aaron Binkley, calling Hammerhead’s approach a way to unlock “the full potential of their data centers.”
And critically, Hammerhead was selected from more than 400 applicants to join SE Ventures’ inaugural Accelerator Program—another validation of the company’s technical and commercial readiness.
The Founding Team: Built for Mission-Critical Environments
Hammerhead’s founding team has a résumé tailor-made for high-stakes, power-constrained infrastructure:
- Rahul Kar (CEO) – Co-founder of AutoGrid; veteran of power orchestration.
- Rajeev Singh (CTO) – Co-founder of AutoGrid; architect of mission-critical, real-time control systems.
- Sadia Raveendran – Led AutoGrid’s partnership with Schneider Electric from investment to acquisition.
Combined, they’ve orchestrated 8,000 megawatts of energy assets across 20+ countries.
The extended leadership team includes veterans from Dell, HPE, Microsoft, Meta, and Lambda Labs—many with deep histories in hyperscale data center operations.
In other words: this isn’t a lightweight founding story.
Why ORCA Could Redefine AI Factory Economics
The economics here are straightforward:
- GPUs are expensive.
- AI factories take years to power and commission.
- Power is the hard cap on growth.
- Every idle minute is lost revenue.
Building more substations or waiting for utility upgrades isn’t a realistic path forward—not at AI’s current pace of demand.
Software that unlocks stranded megawatts immediately, with no new hardware, is the kind of leverage operators dream about.
Hammerhead claims ORCA can:
- Increase token production by up to 30%
- Improve gross margins
- Accelerate workload deployment timelines
- Help operators outpace grid limitations
- Enable new revenue per MW in hyper-tight markets
This isn’t incremental optimization. It’s an architectural shift.
What’s Next: Deployment, Partnerships, and OEM Integrations
With $10M in fresh seed capital, Hammerhead plans to:
- Accelerate product development
- Scale global deployments
- Build deeper OEM partnerships
- Support AI factory operators and hyperscalers
- Develop reference architectures with Schneider Electric
The company is also part of NVIDIA’s Inception Program, hinting that future integrations with GPU-level orchestration may be on the roadmap.
Hammerhead, now emerging officially from stealth, is inviting operators, OEMs, cloud providers, and enterprise AI teams to engage early.
And based on current AI infrastructure constraints, there’s little doubt they’ll have plenty of inbound interest.
The Bottom Line
The GPU supply crunch is real, but the power crunch is even more severe—and far less discussed. Hammerhead AI aims to turn that constraint into an advantage by extracting every possible watt from existing data centers and converting it into productive compute.
If the company’s ORCA platform delivers on its promise, it may help define the next phase of AI infrastructure: power-aware, RL-driven, and ruthlessly optimized for token output.
In a world where megawatts translate directly into model throughput, Hammerhead isn’t just solving a technical bottleneck. It’s reshaping the economics of AI.
Power Tomorrow’s Intelligence — Build It with TechEdgeAI
