As data centres race to support heavier computing demands, power is one constraint that keeps tightening. San Francisco-headquartered PADO AI is stepping into that pressure point with new backing. It has announced a $6 million seed round to expand its orchestration software for data centres trying to do more with limited energy capacity.
The round was led by NovaWave Capital, an LG NOVA-supported fund. The investment will help PADO accelerate product delivery and global market expansion, with a clear focus on the mid-market colocation segment, where operators often face the same energy and efficiency pressures as larger facilities but with fewer resources to manage them.
What challenge does PADO tackle?
PADO AI is fundamentally designed to solve the problem of inaccurate, inefficient, and slow data processing and analysis within complex environments such as data centres. Where traditional systems often introduce unacceptable latency, PADO directly addresses the need for real-time, near-instantaneous analysis and predictive modeling that allows for proactive intervention rather than reactive correction.
A founder with expertise
PADO was founded by Wannie Park in 2025 in San Francisco. He is a seasoned entrepreneur with over 25 years of experience in energy, IoT and SaaS. Wannie has incubated and scaled companies in cleantech and sustainability, delivering three successful exits.
As per the company’s response to TFN, “Prior to founding PADO, Wannie was SVP of Business and Corporate Development at Bidgely, a global AI-powered SaaS provider, CEO of Zen Ecosystems, a leading provider of energy management solutions to SMB and SVP of Business and Corporate Development at Inspire Energy, a leading renewables and sustainability company.”
How was the idea born
Detailing about the motivation behind this idea, the company said it is a mix of both personal experience and market need. Starting off with the market need, the issue of power consumption has long been the primary growth constraint for data centres. This problem became more tangible as AI evolved into a more tangible business lifeline, which in turn led to a doubling down on data centre buildout. Now, there are thousands of legacy data centres sitting idle and new developments that still use the standard “first in, first out” approach to workload scheduling – an approach that isn’t sufficient to support rising AI demand.
The founder told, “I’ve spent about 20 years in energy and commercial SaaS, and that helped me see an untapped market opportunity to develop a solution that could address this power issue and ensure consistent support for AI growth long-term: bridging facilities’ IT systems with their industrial equipment (cooling systems in particular) for more dynamic and intelligent job scheduling, maximised compute, and decreased power usage effectiveness (PUE). The result: more effective use of power by data centres, continued AI support, improved performance, and increase in profit.”
Why is PADO focusing on compute per megawatt?
PADO’s pitch is that data centres should be able to extract more compute from every megawatt they consume. Its software platform is built to orchestrate the moving parts that determine whether a facility runs efficiently or wastes valuable capacity.
This includes power, compute, cooling infrastructure, and distributed energy resources across both white space and gray space environments. By coordinating these systems together rather than treating them as separate operational layers, PADO aims to improve profitability, strengthen resilience, and lift day-to-day efficiency.
This matters at a time when new data centre construction is rising while electricity availability remains a stubborn constraint. AI workloads are intensifying that challenge, pushing facilities to find immediate ways to operate within existing energy limits instead of waiting for grid upgrades or major infrastructure overhauls.
Software that shifts workloads, cooling, and energy strategy
At the core of the platform is workload orchestration powered by AI and machine learning. PADO analyses conditions in real time to recommend when and where compute jobs should run, helping operators improve job packing and shift workloads more intelligently.
Its precision cooling capability adds another layer. Instead of spreading workloads evenly without regard to thermal conditions, the platform identifies where thermal headroom exists and places jobs accordingly. This gives operators a way to increase density without putting unnecessary strain on hotter zones.
PADO also extends beyond compute and cooling into energy strategy. Its software can optimise battery energy storage systems during high-price events, allowing operators to respond more intelligently to changing grid economics. On the compliance side, it automates carbon credit reporting and provides grid stability metrics, helping facilities stay aligned with sustainability targets and evolving regulatory requirements.
Built for a wider market push
The company describes PADO as a workload orchestration venture designed to manage data centre operations by aligning compute demand with power infrastructure, distributed energy resources, and grid services.
PADO is targeting a part of the market that needs practical tools now: colocation operators that must balance rising AI demand, limited electricity, regulatory pressure, and customer expectations all at once.
In that environment, smarter orchestration is becoming less of an upgrade and more of a necessity. PADO is betting that the next advantage in data centres will not come only from building bigger facilities, but from making existing infrastructure work harder, cooler, and more profitably.
Plans ahead
Regarding it’s plans for the next five years, PADO said “We are part of EPRI’s DC Flex working group to partner with the broader AI Data Centre ecosystem to deliver solutions that provide energy flexibility, optimisation while maximising compute. We expect the outcomes of these demonstration projects to help establish different blueprints to drive AI Data Centre growth.”
They continued, “Additionally, we expect to invest in and aggressively expand internationally to capture international AI data centre growth driven by the build out of sovereign AI.”
“We are excited to announce this investment, which will enable us to accelerate the delivery of our SaaS platform with a specific focus on increasing GPU utilisation within data centres that operate under an existing infrastructure and power envelope delivering immediate returns without having to wait for increased power allocations,” said Wannie Park, CEO and Co-Founder, PADO. “While hyperscalers may be driving current large-scale data centre demand, there is an increasing need from enterprise customers who require high power compute but not their own built-to-suit facility. The resulting orchestration opportunity within mid-market data centres is significant, and one PADO’s solutions can readily address without immediate CAPEX needs or increased power requirements.”
“Our goal at NovaWave Capital is to support high-growth AI companies and drive positive change within the energy and business sectors,” said Ali Diallo, Founding Managing Partner, NovaWave Capital. “PADO is a catalyst for the data centre market’s growth and we’re excited to continue supporting the team’s mission to ensure infrastructure can adapt to power constraints while supporting ongoing AI innovation.”
