Traditional AI inference workloads are conducted in energy-intensive cloud data centres. EnCharge wants to change this, shifting workloads to local devices to reduce energy consumption while improving security, latency, and cost-efficiency.
Tiger Global led the Series B round, which brought EnCharge’s total funding to more than $144 million. Other investors backing the startup in its latest round included Samsung Ventures, HH-CTBC (a Foxconn-CTBC VC partnership), Maverick Silicon, and SIP Global Partners.
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EnCharge claims its noise-resilient analogue in-memory compute architecture is designed to reduce energy consumption for AI workloads up to 20 times compared to today’s leading AI chips.
Paired with a platform of software tools designed to maximise efficiency, EnCharge markets its hardware as a cost-effective alternative to powering AI workloads.
The startup plans to use the funds to support the rollout of its first AI accelerator solutions.
“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,” said Naveen Verma, CEO and co-founder of EnCharge. “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.”
The startup has its eye on challenging the AI inference status quo, and has already secured a partnership with Princeton University to develop processors to power AI models, a project that’s being supported by the US Defense Advanced Research Projects Agency (DARPA) .
EnCharge is bolstered by an advisory board of silicon veterans, including Donald Rosenberg, Qualcomm’s former general counsel, Lumotive CEO Sam Heidari, and Andrea Goldsmith, Princeton University’s Dean of Engineering and Applied Science and an Intel board member.
“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,” said Manish Muthal, senior managing director at Maverick Silicon. “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.”
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