Following years of research and development at Princeton University, EnCharge AI emerges from stealth led by a world-class, multi-disciplinary team from Meta, NVIDIA, Qualcomm, and IBM
EnCharge AI, the company building advanced computers for AI at the Edge, announced it has raised $21.7M in Series A financing, led by Anzu Partners with participation from AlleyCorp, Scout Ventures, Silicon Catalyst Angels, Schams Ventures, E14 Fund, and Alumni Ventures. EnCharge will leverage the funding to further develop and commercialize its semiconductor hardware and software stack that offers the highest reported efficiency for AI compute to date.
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“In order to keep pace with the incredible innovations we are seeing in AI, we need fundamentally new ways of computing”
EnCharge’s transformative charge-based in-memory computing technology was originally born out of DARPA and Department of Defense funded R&D and has matured through six years of deep research and validation. This has resulted in demonstrations of AI performance with orders-of-magnitude higher compute efficiency and density than has been achieved by both best-in-class digital accelerators, such as GPUs or TPUs, and recent concepts for beyond-digital accelerators, based on optical or analog computing. Several generations of test chips with end-to-end programmable model execution capability have been demonstrated, resulting in impressive technology advantages:
- Highest efficiency reported for AI compute to date – EnCharge test chips and hardware can achieve over 150 TOPS/W for 8-b compute.
- Seamless integration – EnCharge offers a software stack that supports broad AI models and resolutions, while integrating seamlessly into user frameworks and design flows.
- Lower cost for performance – EnCharge will deliver platforms that provide over 20x higher performance per Watt and over 14x higher performance per dollar, compared to the best-in-class digital AI accelerators implemented in the most advanced technology nodes.
With these benefits, EnCharge seeks to unlock the immense potential of AI by making it accessible to power, energy, and space constrained applications at the edge. These capabilities are valuable for market applications such as automotive sensing, advanced manufacturing, smart retail, smart warehouses and logistics, industrial robotics, and drones.
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“In order to keep pace with the incredible innovations we are seeing in AI, we need fundamentally new ways of computing,” said Naveen Verma, Ph.D., CEO and Co-Founder, EnCharge AI. “This requires differentiated technologies, but which are also extensively validated and refined across the entire stack for real-world operation. We believe that EnCharge’s technology is the only robust and scalable form of next-generation in-memory computing. Following this Series A round, EnCharge is now positioned to develop products to engage with customer applications in production at the forefront of AI.”
EnCharge was founded by Verma along with Kailash Gopalakrishnan, Ph.D., who serves as Chief Product Officer, and Echere Iroaga, Ph.D., who serves as Chief Operating Officer. The foundational technology for EnCharge’s products was developed at Princeton University, where Verma has been a Professor of Electrical and Computer Engineering. Gopalakrishnan was formerly an IBM Fellow and led IBM’s AI Hardware and Software efforts. Iroaga brings over 25 years of semiconductor experience, most recently from MACOM, where he served as VP and GM of the Connectivity business unit, and from Qualcomm, where he served as a Director of Engineering. The broader EnCharge AI team has a proven track record of AI semiconductor execution, including executives and engineers from NVIDIA, AMD, Waymo, Intel, Meta, SambaNova, Cerebras, and more.
“As Edge AI continues to drive business automation, there is huge demand for sustainable technologies that can provide dramatic improvements in end-to-end AI inference capability along with cost and power efficiency,” said Jimmy Kan, Ph.D., Partner, Anzu Partners. “EnCharge’s technology addresses these challenges and has been validated successfully in silicon, fully compatible with volume production. We look forward to working further with this world-class team to commercialize this breakthrough technology.”
“The Edge AI chip market has been waiting for a solution that incorporates performance gains with power optimization,” said Joseph Krause, Investor, AlleyCorp. “EnCharge AI has assembled the strongest team capable of using in-memory architectures to build novel chipsets that support superior TOPS/W. We could not be more excited to back this team and their mission.”
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