AnalogAI Selects memBrain™ SAGE Intellectual Property from Silicon Storage Technology® for its First Real-world Edge AI Processors

Rhea-AI Summary

Microchip Technology (MCHP), through its Silicon Storage Technology (SST) subsidiary, licensed its memBrain™ Synaptic Analog Generative Engine (SAGE) neuromorphic hardware IP to AnalogAI for use as the core inference engine in AnalogAI’s first real-world edge AI processors.

AnalogAI’s processors use a proprietary hardware-aware algorithm to train and run inference on-device in real time, targeting ultra‑low‑power edge applications such as environment‑adapting humanoid robots, drones and vehicles. By adopting SST’s SuperFlash®‑based memBrain SAGE IP, AnalogAI aims to deliver analog compute‑in‑memory performance at or below one watt. SST memBrain SAGE IP is deployed on 40 nm and 28 nm processes, with a roadmap that includes 22 nm development and full IP integration services and support.

News Explained

The disclosure remains a development-stage IP selection: AnalogAI is utilizing SST’s memBrain SAGE IP for its first processors while developing new capabilities, so it does not report a completed product launch.

Market Context

MCHP was down 3.67% at the prior close before the IP-selection announcement; current peer data also ...

Analysis

MCHP was down 3.67% at the prior close before the IP-selection announcement; current peer data also showed ALAB down 4.53% and MPWR down 3.48%, placing the announcement against a broadly negative semiconductor backdrop.

Key Figures

Edge AI power target: at or below one watt Bitcell storage: up to 8 bpc Deployed process nodes: 40 nm and 28 nm +1 more

Edge AI power target

at or below one watt

AnalogAI processors using SST memBrain SAGE IP

Bitcell storage

up to 8 bpc

memBrain optimized ESF3 bitcell

Deployed process nodes

40 nm and 28 nm

memBrain SAGE IP development and deployment

Roadmap process node

22 nm

planned memBrain SAGE IP development

Key Terms

neuromorphic hardware, analog compute-in-memory, bitcell, non-volatile storage

4 terms

neuromorphic hardware technical

"SAGE neuromorphic hardware intellectual property (IP) from Microchip Technology"

Specialized computing chips and systems designed to mimic the structure and behavior of the brain by using networks of artificial neurons and synapses to process information in parallel and with low power. Investors care because neuromorphic hardware aims to run certain tasks — like pattern recognition, sensor processing, and real-time decisioning — far more efficiently than conventional processors, affecting costs, performance, and competitive advantage for companies that build or use these systems.

analog compute-in-memory technical

"deliver high levels of analog compute-in-memory (aCIM) performance"

Analog compute-in-memory is a chip design approach that performs calculations directly inside memory arrays using continuous electrical signals (analog values) instead of converting data to and from digital form. It executes common operations for machine learning, like multiply-accumulate, where the data already lives, which cuts the energy and time lost moving data around. Think of it like doing sums inside the spreadsheet cells where the numbers are stored, rather than constantly copying them to a separate calculator. This matters to investors because it can enable faster, lower-power AI and edge devices, affecting chip performance, costs, and market differentiation.

bitcell technical

"memBrain solution optimized ESF3 bitcell which stores up to 8 bpc"

A bitcell is the basic memory cell inside a semiconductor chip that stores one binary digit (0 or 1), implemented with transistors and capacitors in DRAM or with small transistor circuits in SRAM. Investors care because a bitcell’s physical size, speed, reliability and manufacturing yield determine a memory chip’s capacity, performance and production cost—key factors for a semiconductor maker’s product competitiveness and margins.

non-volatile storage technical

"provide reliable, high-performance and low-power non-volatile storage"

Non-volatile storage is a type of computer memory that keeps data safe even when the device loses power, like a filing cabinet that holds documents when you leave the room. It includes technologies used in solid‑state drives and flash memory and matters to investors because it underpins product reliability, data-center capacity and device performance—factors that drive sales, pricing power and long-term support costs.

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Proprietary on-device training built to dynamically adapt to real-world environments

CHANDLER, Ariz., Sept. 15, 2026 (GLOBE NEWSWIRE) -- AnalogAI has chosen memBrain™ Synaptic Analog Generative Engine (SAGE) neuromorphic hardware intellectual property (IP) from Microchip Technology’s (Nasdaq: MCHP) Silicon Storage Technology® (SST®) subsidiary for its real-world edge AI processors. AnalogAI edge AI processors feature a hardware aware proprietary algorithm designed to simultaneously train and run inference on AI models in real-world environments.

AnalogAI is utilizing SST's memBrain SAGE IP to deliver high levels of analog compute-in-memory (aCIM) performance at or below one watt for ultra-low power edge applications. By leveraging the robust silicon proven SST memBrain SAGE IP based on SST SuperFlash®, AnalogAI is developing new capabilities for real-world inference applications such as environment adapting humanoid robots, drones and vehicles.

“AnalogAI is pursuing innovative co-optimized solutions for edge AI inference that enable edge devices to adapt real-time to sudden changes in the environment,” said Mark Reiten, senior vice president of Microchip’s Intelligent Compute business unit. “As the core inference engine for AnalogAI’s first products, SST memBrain SAGE IP delivers the necessary compute performance coupled with the power efficiency AnalogAI requires to meet their application targets. We are pleased to welcome AnalogAI as the newest licensee of our SST memBrain IP, joining our rapidly expanding ecosystem.”

SST memBrain SAGE IP features:

• memBrain Tensor In-Memory Logic Element (TILE)
  • memBrain solution optimized ESF3 bitcell which stores up to 8 bpc at nanoamp levels
  • memBrain solution custom array, decoders and driver circuitry
• Optimized DACs and ADCs
• Summator and high voltage bias circuitry
• Nanoamp level bitcell control logic
• memBrain proprietary test circuitry
• SST memBrain technology documentation and simulation models
• Full IP integration service and support
  

“AnalogAI selected SST’s memBrain SAGE IP after an industry-wide search of available offerings and determined the silicon-proven memBrain SAGE IP best enabled us to accelerate our development time while still achieving the ultra-low-power and high performance required in our market segment,” said Jaejun Lee, AnalogAI’s chief executive officer. “Analog Compute-in-Memory is a rapidly emerging field, and at AnalogAI we are pioneering new functionality for edge AI devices requiring real-world adaptation.”

SST’s memBrain SAGE IP has been developed and deployed in 40 nm and 28 nm foundry processes using production-ready SuperFlash memory. The current technology roadmap includes 22 nm memBrain SAGE IP development. Designed to provide reliable, high-performance and low-power non-volatile storage directly on the chip, SuperFlash memory is widely used in applications that require fast access times, high endurance and data retention without the need for external memory components.

Pricing and Availability
Customers interested in SST’s memBrain IP solutions and SuperFlash technology should access the SST website or contact a regional SST sales executive for details. Those interested in AnalogAI’s products should visit the AnalogAI website or contact the AnalogAI team at contact@analog-ai.com.

Resources
High-res images available through Flickr or editorial contact (feel free to publish):

• Application image: www.flickr.com/photos/microchiptechnology/55472818028/sizes/o/
  

About Microchip Technology:
Microchip Technology Inc. is a broadline supplier of semiconductors committed to making innovative design easier through total system solutions that address critical challenges at the intersection of emerging technologies and durable end markets. Its easy-to-use development tools and comprehensive product portfolio supports customers throughout the design process, from concept to completion. Headquartered in Chandler, Arizona, Microchip offers outstanding technical support and delivers solutions across the industrial, automotive, consumer, aerospace and defense, communications and computing markets. For more information, visit the Microchip website at www.microchip.com.

About Silicon Storage Technology (SST):
Microchip Technology’s SST subsidiary is a leading provider of embedded flash technology. SST develops, designs, licenses and markets a diversified range of proprietary and patented SuperFlash memory technology solutions for the consumer, industrial, automotive and Internet of Things (IoT) markets. SST was founded in 1989, went public in 1995 and was acquired by Microchip in April 2010. SST is now a wholly owned subsidiary of Microchip and is headquartered in San Jose, Calif. For more information, visit the SST website at www.sst.com.

About AnalogAI:
AnalogAI builds edge AI processors that train directly on the device, allowing robots, drones and vehicles to adapt to changing physical environments in real time while running at ultra-low power. Its analog compute-in-memory architecture performs on-device training and inference in a single low-power design, moving beyond the inference-only approach of conventional edge AI hardware. AnalogAI targets physical-world edge applications where systems must keep adapting after deployment, from robotics to autonomous machines. The company is headquartered in the Seoul area, South Korea. For more information, visit www.analog-ai.com.

Note: The Microchip name and logo, the Microchip logo, Silicon Storage Technology, SST and SuperFlash are registered trademarks of Microchip Technology Incorporated in the U.S.A. and other countries. memBrain is a trademark of Microchip Technology Inc. in the U.S.A. and other countries. All other trademarks mentioned herein are the property of their respective companies.

Editorial Contact:	Partner Media Contact:
Brian Thorsen	Jaejun Lee
480-792-7182	jaejun.lee@analog-ai.com
Brian.Thorsen@microchip.com

This press release was published by a CLEAR® Verified individual.

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What capabilities does SST’s memBrain SAGE IP provide for AnalogAI’s edge AI processors?

SST’s memBrain SAGE IP provides an analog compute‑in‑memory architecture that supports simultaneous on‑device training and inference at ultra‑low power. It includes memBrain Tensor In‑Memory Logic Elements (TILE), custom arrays with ESF3 bitcells storing up to 8 bits per cell at nanoamp levels, optimized DACs and ADCs, summator and high‑voltage bias circuitry, nanoamp‑level control logic, proprietary test circuitry, plus documentation, simulation models and full IP integration service.

Which semiconductor process nodes are used for memBrain SAGE, and what is planned next?

SST’s memBrain SAGE IP has been developed and deployed in 40 nm and 28 nm foundry processes using production‑ready SuperFlash® memory. The current technology roadmap includes development of 22 nm memBrain SAGE IP.

What types of applications are AnalogAI and SST targeting with this edge AI solution?

The companies are targeting physical‑world edge applications that must adapt after deployment, including environment‑adapting humanoid robots, drones and vehicles, as well as other robotics and autonomous machines that require real‑time on‑device learning at very low power.

How can customers learn more or engage with SST and AnalogAI?

Customers interested in SST’s memBrain IP solutions and SuperFlash technology are directed to the SST website or to contact a regional SST sales executive for details. Those interested in AnalogAI’s products are directed to visit the AnalogAI website or contact the company at contact@analog-ai.com.