AI chip startup Velaura AI has raised $110 million in a Series A funding round, pushing the company’s valuation above $1 billion as investors bet on energy-efficient computing for the next generation of AI data centers.
The funding is significant because the AI industry is facing a major challenge beyond model performance: power consumption. As AI data centers become larger, the electricity required to run them is becoming one of the biggest costs and limitations.
Velaura is building technology designed to reduce that power demand.
Velaura AI’s $110M Funding Round
The Series A round was led by Seligman Ventures.
New investor Capricorn Investment Group also participated, alongside existing investors including:
- Samsung Catalyst Fund
- StepStone Group
- Maverick Silicon
The funding values Velaura AI at more than $1 billion.
The company plans to use the new capital to accelerate product development and deployment while expanding its engineering and customer-facing teams.
What Does Velaura AI Build?
Velaura AI develops low-power semiconductor and software technology designed for AI computing.
Its technology is aimed at reducing the amount of electricity required to run AI workloads.
This is becoming increasingly important because AI systems require huge amounts of computing power.
Large data centers are being built to support:
- AI model training
- AI inference
- AI agents
- Robotics
- Autonomous systems
- Cloud applications
All of these workloads require electricity.
Velaura believes its technology can help customers get more computing performance while using less power.
From Auradine to Velaura AI
Velaura AI is actually a new chapter for a company previously known as Auradine.
The company changed its name to Velaura AI in March 2026 as it shifted its focus more strongly toward ultra-low-power computing for AI. The company says its technology is designed for cloud, edge and physical AI applications.
The rebranding reflects the company’s growing focus on the energy problem created by AI.
Velaura says its technology has already been field-tested across tens of millions of ASICs.
Velaura’s Titan Core Platform
Earlier this year, Velaura announced Titan Core, its proprietary chip-design platform.
The technology is designed to help improve efficiency and reduce power consumption in data-center workloads.
Instead of simply trying to build another AI chip, Velaura is focusing on the underlying design technology that can help make computing hardware more energy efficient.
This could become particularly valuable as AI infrastructure becomes more expensive to power.
AI Data Centers Have a Power Problem
AI models are becoming more powerful, but that progress comes with a cost.
Modern AI data centers can contain thousands of advanced processors running around the clock.
The power required for these facilities comes from:
AI chips + memory + networking + cooling + storage
As companies deploy more AI agents and applications, the amount of computing required could grow even further.
This means that improving energy efficiency could become just as important as improving raw computing performance.
Velaura is betting on this shift.
Velaura Is Already Working With Major Chip Customers
The company says its technology has already been deployed in more than 30 million chips.
Velaura is also engaged with three of the four largest cloud computing providers as potential customers, according to CEO Rajiv Khemani, although he did not identify the companies.
If those discussions turn into large commercial contracts, they could significantly increase Velaura’s presence in the AI infrastructure market.
A Different Business Model
Velaura is also using an interesting pricing model.
The company charges customers an upfront technology fee and then collects a royalty based on a portion of the power savings generated by its technology.
Khemani compared the structure to Arm’s earlier licensing model, where the company earned money from chip designs through licensing and per-chip economics.
This model gives Velaura an incentive to help customers achieve measurable energy savings.
If customers save more power, Velaura can potentially earn more.
AI and Robotics Could Both Benefit
Velaura isn’t targeting only traditional data centers.
Its technology is also designed for physical AI applications, including robotics and autonomous systems.
That could become another major market.
Robots need to process information locally to understand their surroundings and make decisions.
Reducing the power required for that computing could help improve:
- Battery life
- Operating time
- Performance
- Heat management
- Hardware size
This could be particularly useful for autonomous robots and other edge AI systems.
Why Investors Are Interested
The funding comes at a time when investors are pouring billions into AI infrastructure.
Companies such as Nvidia are building increasingly powerful processors, while startups are developing specialized chips and technologies for different AI workloads.
But there is a growing realization that simply adding more computing power is not enough.
AI infrastructure must also become more efficient.
Velaura’s pitch is built around this problem.
The company believes the next phase of AI will require better economics, not just bigger models.
Velaura Is Not Trying to Replace Nvidia Overnight
It would be misleading to describe Velaura as a direct replacement for Nvidia.
Nvidia builds some of the world’s most widely used AI accelerators.
Velaura is taking a different approach by focusing on ultra-low-power semiconductor design and infrastructure technology.
Its technology could potentially work alongside larger AI hardware ecosystems rather than replacing them completely.
The bigger opportunity is making the entire AI computing stack more energy efficient.
The AI Infrastructure Race Is Changing
The first phase of the AI boom was largely about building better models.
Then the focus shifted toward building massive amounts of computing infrastructure.
Now another question is becoming increasingly important:
How much does it cost to run all this AI?
Power is a major part of that equation.
A data center that can perform the same amount of AI work while using significantly less electricity could have a major economic advantage.
That is the market Velaura is targeting.
What Happens Next?
Velaura plans to use its new funding to speed up development and deployment of its AI products while hiring more engineers and customer-facing employees.
The company’s ability to turn its technology into large commercial deployments will be the key test.
If major cloud providers and AI hardware companies adopt its technology, Velaura could become an important part of the AI infrastructure ecosystem.
But semiconductor markets are highly competitive, and proving energy savings at scale will be critical.
The Bigger Picture
Velaura AI’s $110 million Series A and more than $1 billion valuation show that investors are increasingly looking beyond AI models and toward the infrastructure needed to run them.
AI data centers are becoming larger, more powerful and more energy hungry.
That creates a huge opportunity for companies that can improve computing efficiency.
Velaura’s strategy is simple but important:
More AI computing with less power.
If the company can deliver on that promise at large scale, its technology could become valuable across data centers, cloud infrastructure, robotics and other physical AI systems.
The AI race is no longer just about who builds the smartest model.
It is also about who can run those models most efficiently.
And Velaura AI is betting that energy-efficient computing will become one of the most important parts of that race.
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