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EdgeCortix Unveils RAIDEN, a Scalable, Energy-Efficient AI Chiplet Platform Purpose-Built for Physical AIPhysical AI has a system problem. Machines that perceive, reason and act in the real world cannot scale by adding AI accelerators alone. Compute, memory capacity, memory bandwidth, connectivity, and software must scale together and continue scaling as the AI models and application workloads evolve. Today, EdgeCortix®, a leading Japanese fabless semiconductor company specializing in energy-efficient AI processing, unveiled RAIDEN™, its next-generation scalable AI chiplet platform purpose-built to address that challenge. Through this chiplet platform, RAIDEN carries EdgeCortix's energy-efficient design into a new performance class, scaling to meet the demands of Physical AI deployed outside centralized data centers. RAIDEN introduces a unified, energy-efficient architecture that scales from a single compute die to a four-die flagship within one hardware and software platform. At maximum scale, RAIDEN is architected to deliver up to 3.36 PFLOPS (3,360 TFLOPS) of FP4 AI compute, up to 256 GB of memory, 548 GB/s of memory bandwidth and up to 1.54 TB/s of aggregate die-to-die bandwidth, together with configurable power settings and up to 6.4 Tb/s of chip-to-chip scale-out connectivity for scaling beyond a single package. RAIDEN is entering the market with customer design wins already secured, spanning demanding Physical AI applications from next-generation aerospace and defense systems, robotic platforms, to high-performance edge AI servers.
One Architecture. From One Die to Four.
All three configurations share EdgeCortix's latest DNA-X® accelerator architecture and MERA™ software stack. Compute, memory capacity, memory bandwidth and inter-die bandwidth scale with the platform, allowing customers to address different performance, power and deployment requirements without moving to an entirely different AI architecture or software environment. This common architecture is designed to allow customers to move across RAIDEN configurations while preserving their software investment and application environment. Detailed specifications and deployment positioning for the X1 and X2 configurations will be introduced in subsequent phases of the RAIDEN launch program.
Four Dies. One AI System to Run the Entire Workload.
The RAIDEN X4 flagship configuration enables:
RAIDEN's scalable chiplet architecture is designed to address this continuum through a common platform, scaling heterogeneous compute, memory and connectivity from a single die to four dies while maintaining a common software environment. For applications that require additional system-level scale, RAIDEN's high-speed chip-to-chip connectivity provides up to 6.4 Tb/s of scale-out bandwidth, extending the architecture beyond an individual multi-die package. The architecture helps reduce the system-level compromises that increasingly constrain advanced Physical AI workloads: swapping models and data between internal and external memory, aggressive quantization, AI and non-AI workload partitioning, and the need to divide a single Physical AI pipeline across multiple discrete computing systems.
Purpose-Built for AI That Perceives, Reasons and Acts.
A single MERA software stack provides a common development and deployment environment across the RAIDEN family, allowing models, tools and software investments to carry across different platform configurations. The same stack spans EdgeCortix product generations, so work done on SAKURA-II today carries forward to RAIDEN rather than being rebuilt. "Physical AI will not be won by simply building a faster accelerator. It requires a platform where compute, memory, bandwidth, connectivity and software scale together - and where the hardware deployed today can run the models customers adopt years from now," said Dr. Sakyasingha Dasgupta, Founder and CEO of EdgeCortix. "That is what we built RAIDEN to do. One architecture and one software platform scaling from a single die inside an intelligent machine to a four-die flagship for the most demanding Physical AI workloads. Most importantly, customers are already designing around RAIDEN." RAIDEN extends EdgeCortix's vision of Powering AI That Acts™ beyond traditional edge inference into a broader class of Physical AI systems, spanning robotics and autonomous systems, intelligent manufacturing, telecommunications, aerospace and defense, and edge AI infrastructure.
Customers Are Already Designing Around RAIDEN.
Kawasaki Heavy Industries, Ltd., has selected RAIDEN-based solutions for multiple next-generation AI-enabled aerospace and defense products, where computing platforms must operate under demanding system constraints while supporting complex AI workloads that continue evolving throughout long product lifecycles. Unigen Corporation, a U.S. headquartered enterprise hardware provider, is developing RAIDEN-based server platforms, expanding an existing collaboration with EdgeCortix that today ships SAKURA-II-powered modules and server systems. Together, these customer engagements demonstrate the breadth of the architecture RAIDEN was created to address: from AI deployed directly within intelligent and autonomous machines to high-performance multi-die systems for on-premise and edge AI infrastructure. Further RAIDEN design wins, application categories, and ecosystem partners will be announced as the program progresses.
Availability and RAIDEN Early Access Program.
Register your interest in the RAIDEN Early Access Program: https://www.edgecortix.com/en/raiden-early-access-program Learn more about RAIDEN: https://www.edgecortix.com/en/products/raiden RAIDEN, EdgeCortix next-generation chiplet solution, is based on results obtained from the project, 'Research and Development Project of the Enhanced Infrastructures for Post-5G Information and Communication Systems' (JPNP20017), subsidized by the New Energy and Industrial Technology Development Organization (NEDO).
About EdgeCortix Inc.
For more information, please visit https://www.edgecortix.com/en/
View source version on businesswire.com: https://www.businesswire.com/news/home/20260923260504/en/ |

