analog.ai is for sale

analog.ai names a chip architecture with peer-reviewed physics behind it and fresh commercial capital in front of it. IBM published an analog-AI inference chip in Nature that packs 35 million phase-change memory devices and runs speech recognition more than 14 times more energy-efficiently than comparable digital hardware. In February 2025, Princeton spinout EnCharge AI raised over $100 million from Tiger Global to commercialize analog in-memory accelerators it claims cut AI energy use by up to 20x. Analog AI is a defined technical category in research papers and startup financing.

Peer Reviewed Analog AI chips in Nature and Nature Electronics IBM published a 2023 Nature paper on an analog-AI inference chip with 35 million phase-change memory devices across 34 tiles, up to 12.4 TOPS/W, and more than 14 times the energy efficiency of digital comparison hardware on speech recognition.

Capital EnCharge: $100M+ Series B, $144M+ total funding TechCrunch reported EnCharge AI raised more than $100 million in a February 2025 Series B led by Tiger Global to accelerate AI using analog chips, and reported the company claimed up to 20x lower energy than other chips.

Product Analog in-memory acceleration moved from lab result to product line EnCharge AI said its February 2025 Series B brought total funding above $144 million and described EN100 as an AI accelerator based on precise, scalable analog in-memory computing with 200+ TOPS for client-computing power budgets and backers including Samsung Ventures, RTX Ventures, In-Q-Tel, and a Foxconn-affiliated fund.

Peer Reviewed

Analog AI chips in Nature and Nature Electronics

IBM Research published an analog inference chip in Nature achieving up to 12.4 TOPS/W, and a 64-core phase-change-memory chip in Nature Electronics demonstrating near-software-equivalent inference accuracy — two peer-reviewed demonstrations for an alternative AI compute architecture.

Capital

EnCharge: $100M+ Series B, $144M+ total funding

EnCharge AI closed an oversubscribed $100M+ Series B led by Tiger Global in February 2025, bringing total funding above $144 million, with backers including Samsung Ventures, RTX Ventures, In-Q-Tel, and a Foxconn-affiliated fund.

Product

Analog in-memory acceleration moved from lab result to product line

EnCharge describes its EN100 as an AI accelerator built on precise, scalable analog in-memory computing and says it delivers 200+ TOPS within laptop-class power budgets. The claim moves analog AI from a research architecture into a shipping product category.