Everspin introduces a new MRAM code and data unified memory for embedded systems

Everspin Technologies launched a new family of unified code and data memory devices, branded as UNISYST MRAM. The new technology and platform targets high-density, non-volatile architecture for edge AI, industrial and mission-critical designs

Everspin's president and CEO, Sanjeev Aggarwal, says that sSystem designers are running into the physical and performance limits of NOR flash, especially as process nodes move below 40 nanometers and workloads become more demanding. With UNISYST, Everspin is extending its MRAM roadmap to higher densities while giving customers a practical way to start with PERSYST today and migrate to a code-and-data MRAM architecture as soon as it is available.

 

Everspin will initially offer the UNISYST family in densities ranging from 128 megabits to 2 gigabits, using a standard xSPI interface operating up to octal SPI at 200MHz. The devices are planned to feature AEC-Q100 Grade 1 qualification and minimum 10-year data retention at extreme temperature, supporting demanding environments across automotive, aerospace, industrial and edge AI applications. Everspin says that engineering samples of UNISYST are expected to be available in the fourth quarter of 2026, with additional densities and options to follow.

UNISYST builds on Everspin’s proven MRAM foundation with capabilities designed to support more complex, software-defined systems:

  • Code-and-data MRAM architecture designed as a next-generation alternative to other non-volatile memory
  • Standard xSPI interface operating up to octal SPI at 200MHz
  • Read bandwidth of up to 400 MB/s and write bandwidth of approximately 90 MB/s, over 400 times faster than NOR flash
  • Write endurance up to 10 times higher than typical NOR
  • AEC-Q100 Grade 1 qualification and minimum 10-year data retention for high-reliability designs

UNISYST is aimed at applications where non-volatile memory must combine high bandwidth, high endurance and predictable behavior over temperature and time. Target use cases include:

  • AI at the edge: Fast AI weight updates, critical storage at the edge, local code-and-data storage for workloads that need fast boot, rapid reconfiguration and non-volatile operation close to the sensor, with the ability to execute in place removing the need for multiple system memories
  • Military and aerospace: Field-programmable gate array (FPGA) configuration and code storage for mission-critical systems, including low-Earth orbit satellites and other platforms that require frequent over-the-air updates
  • Automotive: Control, logging and configuration memory in systems that must meet Grade 1 temperature requirements and long-term data retention
  • Industrial and casino gaming: High-traffic logging and configuration in environments that demand fast writes, long endurance and persistent storage supporting data logging

Disclosure: the author of this post holds shares at Everspin

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Posted: Mar 10,2026 by Ron Mertens