EnCharge AI, a semiconductor startup developing analog memory chips for AI applications, has raised over $100 million in Series B funding.
The round was led by Tiger Global, with participation from Maverick Silicon, Capital TEN, SIP Global Partners, Samsung Ventures, and RTX Ventures.
Optimizing AI with Energy-Efficient Analog Chips
EnCharge AI, spun out of Princeton University, is developing low-power AI accelerators designed to run AI inference tasks directly on laptops, desktops, mobile devices, and wearables—without relying on cloud-based GPUs.
Compared to traditional digital chips, EnCharge claims its analog AI processors:
- Use 20x less energy for AI workloads
- Eliminate memory bottlenecks by integrating compute and storage
- Reduce hardware costs, making AI more accessible at the edge
The company plans to launch its first-generation analog AI chips later this year, manufactured by TSMC, the world’s largest chip foundry.
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Strategic Backing & National Security Interest
EnCharge’s funding round attracted investment from government-linked firms, including In-Q-Tel (CIA-backed VC) and DARPA, signaling U.S. interest in domestic AI chip innovation.
CEO Naveen Verma emphasized the national security importance of AI hardware:
“The U.S. has identified chips and infrastructure as critical to global competitiveness, and we’re proud to be at the forefront of that effort.”
Competition & Future Outlook
EnCharge joins a growing field of analog AI chip startups, including Mythic and IBM Research, which are also developing low-power AI inference solutions.
With AI compute demand skyrocketing, EnCharge’s technology has the potential to reshape the AI hardware market, making AI cheaper, faster, and more energy-efficient for businesses and consumers alike.
