Myth: Reducing power in battery constrained Physical AI applications means sacrificing performance. Reality: Physical AI demands a different approach to compute, one designed to deliver the performance autonomous systems require within tight power and thermal constraints. But power is only one part of the challenge. Physical AI compute also needs to address latency, memory, and safety to support increasingly capable robots and drones operating in the physical world. For @Velaura_AI, that means rethinking the compute architecture itself to meet those demands together, not in isolation.

As @Velaura_AI works to evolve compute for the next era of AI, we’re excited to bring our technology, vision, and mission to a broader audience with @racepointglobal as our partner. Read more about the work we’ll be doing together here: businesswire.com/news/home/2…

At @Velaura_AI, we’re building breakthrough technology to address one of the defining constraints on the next era of AI: power. As our CEO, Rajiv Khemani, shares, meeting the growing demand for compute will require new approaches across hyperscale data centers and Physical AI systems. If you are eager to solve meaningful problems and make an outsized impact, join us in working on one of computing’s most consequential challenges. Explore open roles: jobs.lever.co/velaura/

Few companies are positioned to address AI power consumption across data center and Physical AI applications, and @Velaura_AI is one of them. @Velaura_AI co-founder and president Sanjay Gupta spoke with Max Maxfield of EE Journal about Velaura’s patented ultra-low-power technology, our engagements with hyperscalers, and the growing need to dramatically reduce power for AI compute. Read the full piece on Velaura’s technology, strategic vision, and approach to powering AI from hyperscale data centers to Physical AI systems: eejournal.com/article/new-se…

Great to see the @Velaura_AI India team spending time together outside the office. Team dinners like this are a great opportunity to connect, catch up, and enjoy time together beyond the day to day. Building strong teams and a collaborative culture is an important part of how we work at @Velaura_AI, wherever our teams are based. #VelauraAI #IndiaTeam #LifeAtVelaura

We’re excited to welcome Niken Jariwala as AI Systems Architect at @Velaura_AI. Niken brings nearly two decades of experience spanning AI accelerator architecture, SoC design, CPU architecture, RTL development, and design verification. His career includes leadership and technical roles at Persimmons AI, Analog Devices, Flex Logix Technologies, @intel, @Synopsys, and @SanDisk. Previously, he held engineering leadership roles at @ADI_News and @efpga, where he worked on AI and edge inference accelerator SoCs and IP, including hands-on architecture work for tensor processing, inference, and DSP systems. He also led the RTL & Verification team for an AI edge inference SoC through first-silicon success. Niken’s depth of experience across AI hardware, system architecture, and silicon implementation will be instrumental as we continue developing ultra-low-power technology for data center and Physical AI applications. Please join us in welcoming Niken to @Velaura_AI.

At @Velaura_AI, we’re looking for engineers and technical leaders ready to take on the challenges of power efficiency, AI performance, real-time responsiveness, and functional safety. For @Velaura_AI’s Chief Development Officer, Manu Gulati, taking on these challenges starts with building the right team. Explore open roles and join us: jobs.lever.co/velaura/

Thank you to @Nasdaq for recognizing @Velaura_AI's $110M Series A and celebrating this milestone on the @Nasdaq Tower. The financing reflects continued conviction in Velaura’s technology, team, and vision to advance ultra low power compute for data center and Physical AI applications. We’re grateful to our investors, partners, and team for the continued support behind this milestone.

In his interview with Gemma Allen from @theCUBE x @NYSEWired, @Velaura_AI co-founder and president Sanjay Gupta highlighted how Velaura is approaching Physical AI with ultra-low-power silicon and software designed for the constraints of real-world systems. As AI moves into the physical world, robots, drones, and other autonomous systems require a new approach to compute. Power, thermals, and real-time responsiveness become increasingly important as these systems operate in dynamic environments with more intelligence running directly on-device. Watch Sanjay's full interview here: piped.video/watch?v=tWNRdZ73… Thank you again to @GemmaAllenSays, @bjbaumann2014, @furrier, @NYSEWired, and @SiliconANGLE & @theCUBE for the conversation.

Our $110M Series A financing and valuation exceeding $1B are being celebrated by @NYSE. This milestone reflects conviction in @Velaura_AI's technology and team as we advance ultra-low-power compute across hyperscale data centers and Physical AI. We’re proud to be working alongside the investors, partners, and supporters helping us build on this momentum. Thank you to the @NYSE team.

Check out @Velaura_AI featured in the ‘New Money’ section of the @WSJ Pro for our $110M Series A financing and $1B+ valuation. Beyond mention of our new unicorn valuation, the piece makes note of our ultra-low-power silicon and software technologies for AI data center and physical AI applications. Read the full newsletter here: createsend.com/t/d-3527AA9F8…

Sanjay Gupta, @Velaura_AI's President of Strategy & GTM, is joining @NYSEWired's AI Factory Series live from the New York Stock Exchange today. He’ll sit down with @furrier of @SiliconANGLE & @theCUBE and @bjbaumann2014 of @NYSEWired to talk about where AI compute is headed, the rise of Physical AI, and why ultra-low-power technology is becoming increasingly important as data centers and silicon evolve for the AI era. Tune in live at 8:30 AM PT / 11:30 AM ET and follow @NYSEWired for more. #NYSEWired #theCUBE #SiliconANGLE #VelauraAI

Did you see @velaura_ai during your Bay Area commute down US-101? If not, now’s your chance. Most billboards on 101 promote bigger AI promises, but ours is doing something different. While other billboards scream for more, we’re advocating for less: less power, that is. Velaura AI is advancing ultra low power technology to improve performance per watt across AI data centers and power constrained physical AI applications. If you're driving through the Bay Area on US-101, look up (safely) and find the @velaura_ai billboard for a limited time! #NYSE #VelauraAI #Funding

We’re proud to have the @NYSE recognize this milestone for @velaura_ai following our $110M Series A financing at a valuation exceeding $1B. Thank you to the @NYSE team and to everyone who has been part of the journey so far. We’re just getting started. #NYSEWired #VelauraAI #Funding

Today’s @Reuters exclusive takes a closer look at what we’re building at Velaura and why compute economics will define the next phase of AI. @velaura_ai AI CEO Rajiv Khemani spoke with Reuters about our engagements with three of the four largest cloud providers, our business model, and the opportunity to reduce the power and cost of AI infrastructure. Read Reuters' full exclusive: reuters.com/legal/transactio…

Myth: AI data center power demand is determined by compute power alone. Reality: Total power demand extends beyond the XPU load to the cooling, power delivery and supporting infrastructure needed to support high-density AI compute. @velaura_ai's Titan Core™ solution is designed to significantly lower chip-level power consumption, which in turn reduces heat generation and cooling requirements. The result: less infrastructure overhead and more compute within the same power envelope.

We're delighted to welcome ChinniKrishna Kothapalli as Principal NPU Architect at @velaura_ai. ChinniKrishna brings more than a decade of experience spanning AI hardware architecture, deep learning acceleration, performance modeling, and SoC development. He joins us from @nvidia, where he was a Senior Architect working on HW/SW co-design of next-generation GPU architectures for AI workloads. Before that, he helped shape training hardware at @Microsoft, and at @intel contributed to the architecture of the Nervana Neural Network Processor and designed FPGA-based IP for deep learning inference. ChinniKrishna's expertise at the intersection of machine learning, system architecture, and silicon design will be invaluable as we continue developing next-generation technology for cloud, edge, and Physical AI. Please join us in welcoming ChinniKrishna to @velaura_ai.

Physical AI is where technology is headed, with firms like @PwC projecting the global market will reach nearly $500 billion by 2030. Reaching that market moment will require more than advances in computing performance. The real catalyst for industry growth will be purpose-built architectures designed for the unique demands of Physical AI. Applications like drones and robotics need optimized, power-efficient architectures to process large data sets and real-world environments at the edge, enabling them to act autonomously in real time. Check out @PwC's report for more on the physical AI market:strategyand.pwc.com/de/en/in…