EnCharge AI, a company developing first-of-its-kind analog in-memory-computing AI chips, announced it has raised over $100 million in Series B funding. Tiger Global led this round and the new financial investors included Maverick Silicon, Capital TEN, SIP Global Partners, Zero Infinity Partners, CTBC VC, Vanderbilt University, Morgan Creek Digital, and others. Previous investors participating in the Series B round include RTX Ventures, Anzu Partners, Scout Ventures, AlleyCorp, ACVC, and S5V.
Some notable investors focused on semiconductors and consumer electronics participating in the Series B round include Samsung Ventures, Samsung’s corporate venture capital arm, and HH-CTBC, a partnership between Hon Hai Technology Group (Foxconn) and CTBC VC. These investors, combined with previous investor VentureTech Alliance, provide EnCharge AI with a wealth of insight into future trends, opportunities, and pain points in the semiconductor and consumer electronics industries.
Most AI inference computation is accomplished with large clusters of energy-intensive chips warehoused in cloud data centers, which is environmentally and economically unsustainable. By utilizing dramatic improvements in compute efficiency to move AI inference from the cloud to local devices, EnCharge is enabling entirely new AI experiences outside of the data center while improving security, latency, and cost.
EnCharge AI’s Series B round also included notable strategic investors in defense and industrial technology, reflecting the wide applicability of EnCharge’s innovations across industries. In-Q-Tel (IQT), the not-for-profit strategic investor advancing technologies for the U.S. national security community and America’s allies; RTX Ventures, the venture capital arm of RTX; and Constellation Technology Ventures, the venture capital arm of Constellation.
This new funding will enable EnCharge to bring its first AI accelerator solutions to market and in configurations that meet partner needs. AndEnCharge AI’s noise-resilient analog in-memory compute architecture will dramatically reduce the power requirements of running conventional and generative AI inference workloads.
By integrating highly efficient analog processing and memory simultaneously, EnCharge’s AI accelerators require up to 20x less energy to run AI workloads than leading AI chips available today across a wide range of use cases. Paired with a platform of software tools designed to maximize efficiency, performance, and fidelity, EnCharge AI’s technology will dramatically expand AI capabilities within a given power budget, broadening the reach of AI beyond the data center to edge and client environments.
EnCharge’s technology comes at a notable time for the AI industry, which is grappling with the exponentially growing energy demands for AI computing driven by a wave of generative AI applications.
Along with scaling its initial products, EnCharge AI’s series B round will advance progress along an ambitious product roadmap, which includes moving to advanced technology nodes and offering a portfolio of solutions to tackle AI computing from edge devices to data centers.
This latest funding round, which brings EnCharge AI’s total funding to over $144 million, will advance the commercialization of its first client computing-focused AI accelerator products in 2025 and progress along EnCharge’s future product roadmap.
KEY QUOTES:
“The efficiency breakthrough of EnCharge AI’s analog in-memory architecture can be transformative for defense and aerospace use cases where size, weight, and power constraints limit how AI is deployed today. Continuing our collaboration with EnCharge AI will help enable AI advancements in environments that were previously inaccessible given the limitations of current processor technology.”
- Dan Ateya, President and Managing Director of RTX Ventures
“EnCharge has achieved something revolutionary while having comprehensively derisked their technology through research at Princeton before the company was even launched. Building on multiple generations of chips encompassing seven years of peer-reviewed research, Naveen and his team are ready to commercialize a complete hardware and software solution that can bring advanced AI out of the cloud and onto consumer devices.”
- A managing Director at Samsung Ventures
“When evaluating EnCharge AI, we looked at and beyond their initial product plans and considered how this technology will continue to develop in the future. We were excited by the opportunity EnCharge has to rapidly bring products to market while continuing to achieve efficiency gains with their technology, raising the bar of AI compute efficiency to a place that would be difficult for others to reach.”
- Manish Muthal, Senior Managing Director at Maverick Silicon
“Our Series B is a pivotal milestone for the company that signals our readiness to bring our full stack AI solutions to market in 2025. We are grateful to the fantastic group of investors who will help us unlock the potential of artificial intelligence for countless industries and applications in a way that is sustainable, cost-effective, and scalable.”
- Naveen Verma, CEO and co-founder of EnCharge
“While we are very bullish on AI infrastructure across the spectrum, we believe that client-based inferencing is a critical, rapidly emerging sector. We are confident that EnCharge’s extremely productive and energy efficient solutions will lead the large-scale global adoption of distributed AI compute.”
- Jeffrey Smith, General Partner of SIP Global Partners
