Velaura AI, Inc. (formerly Auradine) announced Titan Core™, a breakthrough silicon design and IP platform engineered to redefine power efficiency for AI accelerators. Titan Core™ enables up to 2x lower overall chip power for AI accelerators, delivering up to 500W of power savings on a typical 1000W GPU or XPU. For hyperscaler data centers, this translates into significant reductions in electricity, cooling, and infrastructure costs, often equating to tens to hundreds of millions of dollars in savings. Additionally, this unlocks the ability for XPU deployment growth that would otherwise be constrained by power availability.

Built on Velaura AI's patented, ultra-energy-efficient digital design technology and validated across over thirty million leading-edge ASICs in production deployments over multiple years, Titan Core™ delivers fundamental innovations to optimize AI compute power.

Velaura AI has ongoing engagements with several leading hyperscaler XPU partners across 3nm and 2nm process nodes and is in discussions to integrate Titan Core™ into next-generation AI accelerators. The company is now expanding its engagement with additional GPU and XPU vendors seeking transformational power-efficiency gains.

Titan Core™: Redefining Power Efficiency for AI Accelerators
As AI workloads scale across data centers worldwide, power, not compute capability, is becoming the limiting constraint. Global AI-related electricity demand is projected to more than double to over 945 TWh/year by 2030 (IEA Report), placing enormous pressure on infrastructure expansion.

Velaura AI is addressing this challenge with its breakthrough silicon technology that dramatically reduces the energy used by AI accelerators. A significant amount of power in modern AI accelerators is consumed by mathematical operations that perform matrix multiplications (MATMUL), the fundamental building blocks of AI training and inference. Titan Core™ reduces the energy required for these operations by 2-4x using proprietary circuit and library technology at advanced semiconductor process nodes. This equates to approximately $1,300 in electricity savings over three years per XPU, in addition to meaningful reductions in cooling and infrastructure costs, ultimately driving substantial improvements in total cost of ownership (TCO).

Integration of Titan Core into customers' existing SoC architectures and design flows is seamless, maintaining full functional equivalence. Velaura starts from the customer's RTL design and applies its proprietary libraries and physical design methodology to deliver an optimized physical layout. The resulting ultra-low-power design operates at a lower voltage and integrates easily into the customer's SOC.

"Our initial engagements with top hyperscalers are validating Titan Core's capability to dramatically reduce global AI data center power costs and improve AI sustainability. The future of AI will be defined by who can deliver the most meaningful performance within real-world power limits. We are excited to unveil Titan Core™, our ultra-low power technology perfected over several years," said Rajiv Khemani, Co-founder and CEO of Velaura AI.

"Power is the binding constraint on AI scale, and the industry has been slow to address it at the silicon level, where it matters most. Velaura AI's approach targets the single largest power consumer inside an AI accelerator - matrix multiplication - using low-voltage design techniques proven across tens of millions of production ASICs. That production track record at 3nm is what separates this from a whiteboard exercise. If the efficiency gains hold up under independent validation, the implications for data center TCO and deployable compute capacity are substantial," said Patrick Moorhead, CEO & Chief Analyst, Moor Insights & Strategy.

"At SemiAnalysis, we track 200+ neoclouds and 6,000+ datacenters globally. Power availability is a key constraint driving half of datacenters expected to go behind-the-meter by 2027. By reducing the energy needed to generate AI tokens, Titan Core is a pragmatic solution that Velaura AI's customers can use to drive efficiency, lower OPEX, and allow more of the total datacenter BOM to be spent on compute." Dylan Patel, Founder and CEO, SemiAnalysis.

A Proven Technology Stack for Low-Voltage Silicon

Delivering ultra-low-power compute requires far more than incremental optimization. It requires deep expertise in custom circuit design and silicon behavior at voltages significantly below nominal GPU and XPU operating levels.

Velaura AI has developed comprehensive, production-proven technology perfected over multiple years that consists of upfront design service and licensable IP, including:

• Proprietary low-voltage digital design libraries at advanced semiconductor nodes, including 3nm, 2nm, and beyond
• Custom Electronic Design Automation (EDA) flows and advanced circuit methodologies optimized for low-voltage design, that deliver world-class yield, reliability, and performance
• Potential silicon area reduction depending on the design targets
• Seamless integration into existing SoC architectures and design flows

The company has demonstrated large-scale production capability by shipping over 30 million energy-efficient ASICs at leading process nodes over several years. This field-proven silicon foundation underpins Titan Core™ for AI accelerators, providing customers with a multi-year time-to-volume advantage versus do-it-yourself (DIY) approaches that carry significant yield, reliability, and schedule risk.

Delivering Real Economic and Deployment Impact
Ultra-low power compute translates directly into measurable infrastructure benefits:

• Expanded AI deployment capacity in power-constrained environments
• Reduced electricity consumption and operating costs
• Decreased cooling requirements, allowing for simpler thermal management
• Increased rack-level compute density within existing power envelopes