Japanese chiplet specialist EdgeCortix has unveiled RAIDEN, a scalable energy-efficient AI chiplet platform designed for physical AI and robotics workloads.
EdgeCortix has unveiled RAIDEN, its next-generation scalable AI chiplet platform designed to address the computational demands of Physical AI deployed outside centralized data centers. The platform carries EdgeCortix's energy-efficient design into a new performance class, scaling from a single compute die to a four-die flagship within a unified hardware and software architecture.
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. 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, and high-performance edge AI servers.
The platform addresses Physical AI at the thick edge—an emerging class of high-performance AI systems deployed outside centralized data centers and closer to machines, sensors, and operational environments. Rather than creating separate architectures for different performance classes, RAIDEN scales through modular chiplet configurations: single-die (X1), two-die (X2), and four-die (X4) flagship. All three share EdgeCortix's latest DNA-X accelerator architecture and MERA software stack, allowing compute, memory capacity, memory bandwidth, and inter-die bandwidth to scale with the platform. This common architecture enables customers to move across RAIDEN configurations while preserving their software investment and application environment.
The RAIDEN X4 flagship operates four compute dies as a tightly integrated system rather than as isolated accelerators. As multimodal, generative, and agentic AI models become part of diverse applications across the Physical AI landscape, systems must simultaneously accommodate larger models, greater context, multiple concurrent workloads, and increasingly demanding real-time constraints—all within practical power envelopes. RAIDEN's scalable architecture addresses this continuum through a common platform while maintaining a unified software environment. For applications requiring additional system-level scale, the platform'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 system-level compromises that 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 systems.
Central to RAIDEN is the latest DNA-X architecture, engineered to execute the full workload while scaling as a unified platform. It maintains the runtime-reconfigurable advantages of earlier generations while introducing micro-code programmable matrix and vector engines, extending versatility beyond standard neural-network inference to support perception, reasoning, application processing, and control workloads operating together within a common scalable platform. The 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," said Dr. Sakyasingha Dasgupta, Founder and CEO of EdgeCortix. "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. 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.
Customer sampling is expected to begin in early 2027, with volume production planned for the second half of 2027. The RAIDEN Early Access Program is now open, giving qualified customers and ecosystem partners an opportunity to engage with EdgeCortix during development and receive priority consideration for customer samples. The program has already generated strong customer interest, building on the design wins secured to date.
RAIDEN 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).
EdgeCortix is a fabless semiconductor company delivering energy-efficient AI compute across edge and Physical AI applications, from embedded devices to on-premise systems. Headquartered in Kanagawa, Japan, with operations in the United States and India, the company develops advanced silicon and software platforms built on its patented hardware-software co-design approach. Its Dynamic Neural Accelerator (DNA) architecture and MERA software stack support inference, generative, and agentic AI workloads on a runtime-reconfigurable platform scaling from the SAKURA-II single-chip accelerators to the RAIDEN multi-die chiplet platform.