EnCharge Secures Over $100M for AI Acceleration with Analog Chips

EnCharge AI, a semiconductor startup spun out from Princeton University, has successfully raised over $100 million in a Series B funding round. This round, led by Tiger Global, aims to fuel the company's next growth phase. The excitement around AI is at an all-time high, yet the steep costs of building and running AI services remain a concern. EnCharge believes its innovative analog memory chips, designed for integration into devices like laptops, desktops, handsets, and wearables, will not only accelerate AI processing but also reduce costs.

Based in Santa Clara, EnCharge claims its AI accelerators consume 20 times less energy than other market-available chips. They anticipate launching their first chips later this year. This funding round is particularly noteworthy as it aligns with the U.S. government's push to enhance domestic innovation in hardware and infrastructure, including chips. Should EnCharge succeed, it could play a pivotal role in this national strategy.

This Series B is a new funding round, distinct from a tranche reported in December 2023. Bloomberg hinted at this Series B last May, noting EnCharge's intention to raise at least $70 million to expand its business. In a conversation with TechCrunch, EnCharge's CEO and co-founder, Naveen Verma, did not disclose the company's valuation, correcting PitchBook data that suggested a $438 million post-money valuation in October as inaccurate.

Verma also kept the identities of EnCharge's customers under wraps, but the diverse group of investors in this round hints at potential partnerships. Alongside Tiger Global, investors include Maverick Silicon, Capital TEN from Taiwan, SIP Global Partners, Zero Infinity Partners, CTBC VC, Vanderbilt University, and Morgan Creek Digital, as well as returning investors like RTX Ventures, Anzu Partners, Scout Ventures, AlleyCorp, ACVC, and S5V.

Corporate investors in the round include Samsung Ventures and HH-CTBC, a collaboration between Hon Hai Technology Group (Foxconn) and CTBC VC. EnCharge has previously received support from the VentureTech Alliance, In-Q-Tel, and Constellation Technology, along with grants from U.S. organizations such as DARPA and the Department of Defense.

Verma mentioned a close collaboration with TSMC, which he said has been following his research for years and provided access to advanced silicon—a rare opportunity. This partnership dates back to the early stages of EnCharge's R&D.

EnCharge's focus on analog technology sets it apart from competitors who primarily target processing chips for AI training and inference at the server level, boosting business for GPU makers like Nvidia and AMD. EnCharge's approach, as detailed in a recent IBM research paper, integrates compute and memory, making these processors more cost-effective than traditional designs. While these chips are suitable for inference at the edge, EnCharge and others like IBM are exploring new algorithms to broaden their applications.

EnCharge isn't alone in pursuing analog technology, but Verma highlights a significant breakthrough in their chip design, making them resilient to noise. This innovation involves using a precise device available in the standard supply chain—geometry-dependent metal wires that can be finely controlled. EnCharge also offers a full-stack solution, including software tailored to its hardware.

Jimmy Kan, an investment partner at Anzu Partners with a focus on semiconductors, noted the crowded field, having reviewed over 50 companies in this space since 2017. He emphasized the search for truly differentiated AI compute technology, expressing excitement about EnCharge's progress.

EnCharge's journey contrasts with many deep tech startups that have emerged over the past few years, often backed by ample venture funding. These startups often focus on ideas that are not yet market-ready but hold significant potential. EnCharge, however, took a more measured approach, emerging from stealth in 2022 after nearly a decade of research at Princeton. This strategy allowed them to de-risk their technology and focus on securing commercial partners while continuing development.

Verma explained that for fundamentally new technologies, understanding and de-risking the technology is crucial before shifting focus to customer needs upon receiving venture funding.