San Jose, June 2026 – Akeana, a provider of Performance-leading RISC-V Processor System IP, today announces a collaboration with Innatera, a leader in neuromorphic computing for the AI sensor edge, to support the development of future edge AI solutions.
“Innatera develops the industry’s most advanced neuromorphic SoCs for high-performance near-sensor AI at the lowest power levels and shortest latencies. Our partnership with Akeana allows us to leverage its RISC-V processor technology as part of our broader architecture, enabling exciting applications in the physical AI space,” says Sumeet Kumar, CEO and Co-Founder of Innatera. “Our mission of processing the world’s data directly at the sensor requires an efficient platform approach in order to scale across a wide variety of use cases. Flexible and scalable CPUs are critical to this mission, and we are excited to collaborate with Akeana.”
This collaboration reflects Innatera’s focus on combining different compute approaches to support a wide range of applications and customer needs while maintaining its commitment to ultra-low-power, real-time intelligence. The flexibility of a processor solution allows Innatera to support a broader range of applications, AI models and customer base as well as better react to customers’ changing requirements.
“Akeana is very proud to be working with Innatera. They are really pushing the boundaries in terms of efficient compute for Edge AI, and we are very excited to be able to support them”, says Rabin Sugumar, CEO of Akeana. “We feel that Innatera really challenges the use case of our AI Vector cores for their ultra-low power products”.
Innatera’s Spiking Neural Processor mimics the brain’s mechanisms for processing sensory data. Based on a groundbreaking computing architecture, Innatera’s processors leverage the computing capabilities of Spiking Neural Networks (SNNs) to deliver ground-breaking cognition performance within a narrow power envelope. With an unprecedented combination of ultra-low power consumption and short response latency, these chips enable high-performance always-on pattern recognition capabilities for power-limited and latency-critical applications.
