Velaura AI, a company developing ultra-low-power silicon and software for AI compute infrastructure, has raised $110 million in Series A funding, bringing its total valuation above $1 billion. The company says the round reflects investor confidence in its established technology, multiple partnerships with major cloud providers, an experienced leadership team, and its vision for AI compute spanning both data centers and what's known as Physical AI, meaning AI embedded in robots, drones, and other autonomous physical systems.
Velaura is targeting two major growth areas tied to AI: ultra-low-power computing and Physical AI. The company argues that AI progress is increasingly limited not by demand for computing power itself, but by the electrical power needed to run that compute. Major cloud providers are investing hundreds of billions of dollars into AI data centers, but often face long lead times just to secure enough power capacity to bring those facilities online. At the same time, as Physical AI systems like robots, drones, and autonomous vehicles move toward mainstream deployment, they operate under strict power and heat constraints, making energy-efficient, purpose-built computing one of the industry's defining challenges.
The Series A round was led by Seligman Ventures, with participation from new investor Capricorn Investment Group, alongside existing investors including Mayfield, Maverick Silicon, MARA, Premji Invest, Samsung Catalyst Fund, and StepStone Group.
Velaura plans to use the new funding to accelerate development and commercialization of its AI compute product lineup, including its recently announced Titan Core silicon platform, while also expanding its engineering and customer-facing teams and deepening partnerships with strategic customers building next-generation AI infrastructure and Physical AI systems.
The company's leadership team brings decades of combined experience building some of the semiconductor industry's leading high-performance and low-power chip platforms, drawing on executives and engineers with backgrounds at Apple, NVIDIA, Google, Qualcomm, and Marvell, along with leaders who have previously built and scaled multiple semiconductor companies and shipped billions of chips.
Velaura's core technology, Titan Core, is a proprietary digital chip design platform that delivers a 2 to 4 times improvement in performance per watt for the mathematical operations used in AI accelerators, without sacrificing performance. The company says this underlying technology has already been validated at commercial scale, having been deployed in more than 30 million ASICs (application-specific integrated circuits) across leading semiconductor manufacturing processes, demonstrating strong manufacturing yield and reliability. Velaura is applying this same expertise to AI accelerators broadly, while extending its ultra-low-power architecture into Physical AI applications like robots, drones, and other embodied AI systems.
Rajiv Khemani, co-founder and CEO of Velaura AI, said every advance in AI, from reasoning models to embodied intelligence, drives demand for more compute, and ultimately more power. He said the next era of AI will be defined not just by better models but by fundamentally better compute economics, and that Velaura is building the ultra-low-power silicon and software foundation needed to scale AI from hyperscale data centers to intelligent machines operating in the physical world.
Patrick Moorhead, founder, CEO, and chief analyst at Moor Insights & Strategy, said AI infrastructure is increasingly constrained by the cost and complexity of delivering more compute, and that Velaura's approach has the potential to improve performance per watt in ways that could lower total cost of ownership, ease thermal constraints, and let companies fit more AI capacity into their existing infrastructure, advantages he described as meaningful for customers trying to scale AI from data centers to autonomous systems.
Umesh Padval, managing partner at Seligman Ventures, said Physical AI represents one of the next major frontiers in AI and will require a fundamentally different approach to computing centered on extreme power efficiency. He described this as the firm's first investment in Physical AI, reflecting its thesis-driven approach to backing category-defining companies, and pointed to the Velaura team's proven expertise in low-power silicon, deep software and systems experience, and technology already deployed in more than 30 million production ASICs as reasons the firm had strong conviction in leading the investment.
Dipender Saluja, managing partner of Capricorn's Technology Impact Funds, said AI's energy footprint is on track to become one of the most significant infrastructure challenges of the decade, and that Velaura is addressing that problem at its root, the silicon itself, with technology that has already shipped at scale. He said the combination of measurable efficiency gains and commercial validation, applied to some of the fastest-growing areas of AI, is exactly what the firm looks for in an investment.
Navin Chaddha, managing partner at Mayfield, said Velaura is making ultra-low-power computing practical for Physical AI while making data center computing dramatically more efficient, addressing two of the most significant opportunities in AI infrastructure. He noted that Mayfield invests in people first, and that this marks the firm's fourth partnership with Khemani and second with co-founder Manu Gulati, having worked with them since Velaura's founding, adding that the firm is excited to support the team as it builds the next generation of energy-efficient AI compute infrastructure.
