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Ainekko Acquires Esperanto Technologies’ Intellectual Property to Power Open-Source Edge AI Platform
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Ainekko Acquires Esperanto Technologies’ Intellectual Property to Power Open-Source Edge AI Platform
Nov 19, 2025 6:24 AM

SAN FRANCISCO, Nov. 19, 2025 (GLOBE NEWSWIRE) -- Ainekko, a startup pioneering open, software-defined AI infrastructure, today announced the acquisition of all intellectual property and select assets from Esperanto Technologies, including chip designs, software tooling, and development frameworks. The acquisition marks a major step toward Ainekko’s goal of making advanced AI infrastructure open, accessible, and adaptable, starting at the silicon level.

By releasing a production-grade, many-core RISC-V architecture to the public, including RTL, reference designs, and development tools, Ainekko is laying the foundation for a new era of community-driven hardware innovation. The platform is designed to empower developers, researchers, and enterprises to experiment, customize, and build their own AI hardware optimized for edge inference.

“We’re building a new kind of AI infrastructure, one that is open, modular, and designed to evolve in the open,” said Tanya Dadasheva, co-founder of Ainekko. “By open-sourcing these assets, we’re enabling developers, researchers, and enterprises to break free from closed ecosystems and innovate directly at the silicon level.”

“This is one of the most ambitious open-source silicon initiatives we’ve seen to date,” said Rich Wawrzyniak, Principal Analyst at The SHD Group. “The many-core RISC-V architecture originally developed by Esperanto is technically impressive and extremely energy efficient. By acquiring and open-sourcing this IP, Ainekko is enabling a wider range of companies to explore custom silicon for AI inference—especially in edge environments where power, cost, and flexibility are critical. It’s a smart way to unlock latent value in a well-architected design.”

While Esperanto focused on large-scale data center deployments, Ainekko believes the real opportunity lies at the edge, where energy efficiency, flexibility, and openness matter most. Esperanto’s core technology was never the problem. The ET‑SoC‑1 chip remains one of the most advanced many-core RISC‑V architectures ever built, featuring more than 1,000 Minion™ cores on a single die, programmable at the instruction level and capable of supporting AI, HPC, and general-purpose workloads. Ainekko is now unlocking that technical value by bringing the platform to a broader audience, from robotics to industrial automation, through a radically open approach. By open-sourcing the RTL and tools and focusing on composable, edge-scale AI infrastructure, Ainekko is enabling developers to realize the potential of what Esperanto created in the environments where it can have the greatest impact.

Ainekko’s platform will build on this architecture and include reference hardware, open development tools, and a growing suite of community resources to support a wide range of applications:

Robotics and drones – Low-power onboard AI for autonomous navigation and real-time controlIndustrial edge systems – Fanless inference engines for manufacturing, automation, and kiosk applicationsSecurity and surveillance – Embedded monitoring and secure edge processingEmbedded and IoT devices – AI-powered inference at the microcontroller levelAcademic and community R&D – Open platform for research, prototyping, and educationMedia processing – High-performance video/audio pipelines powered by parallel coresCustom SoC design – Tailored chips for customers with unique inference needs

Ainekko is also exploring foundation-based governance to ensure long-term transparency and community ownership of the platform.

“What Linux did for servers and what Kubernetes did for the cloud, we believe open hardware can now do for AI inference,” said Roman Shaposhnik, co-founder of Ainekko. “By open-sourcing a fully validated silicon stack, we’re giving the community a foundation to build on, adapt, and own.”

“The architecture developed at Esperanto was ahead of its time: highly efficient, massively parallel, fine grain, agile, and built on a solid foundation of the RISC-V ISA,” said Dr. Allen Rush, former Senior Fellow with AMD, responsible for AI acceleration architecture and strategies for GPU products. “It demonstrated that open, high performance multi-core compute at scale was not only possible but practical. With this acquisition, Ainekko is preserving that legacy and taking it further. By developing a next-generation, open-source platform and extending on these core ideas, Ainekko is opening the door to new levels of performance and software defined flexibility for AI inference applications.”

Ainekko recently launched AI Foundry, an open-source platform designed to make advanced hardware and tooling accessible, modular, and community-driven. The initiative extends open-source principles all the way down to silicon and serves as the hub for developers, researchers, and partners looking to contribute to the future of open AI infrastructure. Join the community at www.aifoundry.org.

Resources

Press Release: Ainekko Launches AI Foundry, Bringing Open-Source Principles and ‘Do-Ocracy’ to AI HardwareCommunity Blog: Esperanto lives on at AINekko About Ainekko

Ainekko is a startup building the first open, software-defined platform for AI infrastructure—extending open-source principles all the way down to silicon. By offering flexible, modular hardware and tooling, Ainekko empowers developers to build efficient, composable AI systems for edge and data center applications alike. Founded by industry veterans with deep expertise in open systems and silicon design, Ainekko is on a mission to make AI hardware accessible, developer-driven, and community-powered. More at www.ainekko.io

Image: https://www.globenewswire.com/newsroom/ti?nf=OTU3ODM5MyM3MjcxODE1IzIzMDY2NTI=

Image: https://ml.globenewswire.com/media/YWUyOTY5NDAtOWMyNC00ODFhLTg0YzktODFkNzZkMDM0MzUzLTEzMTgyMDItMjAyNS0xMS0xOS1lbg==/tiny/Ainekko.png Contact

[email protected] Image: Primary Logo

Source: Ainekko

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