Artificial Intelligence
EdgeCortix Successfully Closes $20 Million Funding Round
EdgeCortix Secures $20 Million Funding Round, Poised to Revolutionize the Edge AI Market
EdgeCortix® Inc., a Japan-based pioneer in edge artificial intelligence (AI) fabless semiconductor development and design, proudly announces the successful closure of a $20 million (approximately ¥3 billion) funding round. Leading the investment is Japan’s renowned venture capital firm, SBI Investment Co. Ltd., along with Global Hands-On VC (GHOVC), a prominent Japan-US collaboration-focused VC known for its successful semiconductor investments. Renesas Electronics Corporation, a premier supplier of advanced semiconductor solutions, has also invested in EdgeCortix, further deepening their strategic partnership in AI/ML (Machine Learning) development. Existing investors Cycle Group and Monozukuri Ventures have joined this funding round as well.
EdgeCortix, founded by CEO Dr. Sakyasingha Dasgupta, is dedicated to redefining the edge AI landscape with its high-speed, ultra-low-power, flexible edge AI-focused processor and an innovative software-first approach. The company’s suite of proprietary software and AI chip products accelerates AI inference tasks for computer vision, natural language processing, and generative AI applications while maintaining very low power consumption and latency. This transformation is particularly relevant for systems operating outside typical data centers, often referred to as “the edge.”
EdgeCortix’s core mission is to democratize access to machine learning solutions by delivering near-cloud-level AI performance at the edge, surpassing conventional GPUs, CPUs, and other processors in terms of performance and energy efficiency by over tenfold.
The company’s unique approach involves a patented AI hardware and software co-exploration process, departing from the traditional method of hardware-first development with software as an afterthought. This integrated solution is crucial as the capabilities of general-purpose processors, such as CPUs and GPUs, struggle to meet the demands of today’s neural networks, especially in deploying generative AI applications.
EdgeCortix will utilize the newly acquired funds to launch the next generation of SAKURA hardware products, expand its global sales and marketing efforts, strengthen its engineering presence in Japan, and establish a new development center in India. The company also plans to strategically recruit top talent in key technology roles to drive innovation in energy efficiency, enabling low-power multi-modal generative AI, automation AI, and efficient language model capabilities for edge devices.
The edge AI inference market, EdgeCortix’s primary focus, is experiencing rapid global growth. By 2025, more than 75% of enterprise-managed data will be generated or processed at the edge, with the total addressable market (TAM) projected to reach $84 billion. The Asia Pacific region, driven by increasing demand for energy-efficient AI processing in commercial, defense, and aerospace applications, is expected to have the highest compound annual growth rate globally from 2022 to 2027.
Dr. Sakyasingha Dasgupta, Founder and CEO of EdgeCortix, expressed, “Our mission is to bring AI acceleration capabilities into complex computing systems at a low cost, with low latency and leading energy efficiency. We are delighted to welcome SBI Investment, GHOVC, and Renesas to the EdgeCortix family. This funding round, coupled with the support of strategic investors, underscores the talent and capabilities of our team and our commitment to enabling low-power AI across the edge ecosystem.”
SBI Investment commented, “The semiconductor sector is a core industry of immense importance, and EdgeCortix is positioned to offer innovative products and services that differentiate it from competitors. Together with EdgeCortix, we will pioneer the future of Edge AI.”
Renesas Electronics Corporation’s Mohammed Dogar added, “EdgeCortix solutions are innovative and highly scalable, and we look forward to expanding our partnership across our collective edge AI-focused product portfolio.”
Shri Dodani, Founder & Managing Partner of GHOVC, noted, “Our team is well positioned to support EdgeCortix in delivering their industry-leading solutions across the globe. EdgeCortix perfectly aligns with our model—a Tokyo-based technology company with a significant global footprint, specializing in innovative hardware and software for edge AI.”
EdgeCortix has introduced three products to the market to date: MERA, its multiple hardware platform-compatible compiler software framework; Dynamic Neural Accelerator (DNA), its scalable, runtime-reconfigurable neural network processor intellectual property (IP); and the power-efficient TSMC 12nm technology-based SAKURA AI co-processor device. Together, these products form an integrated platform suitable for real-time AI applications with streaming data, such as high-resolution cameras, sensors, autonomous robotics systems, signal processing, language models, and multi-model generative AI-based systems. The EdgeCortix Edge AI platform excels in AI inference capabilities across power and mobility-sensitive devices like aerial, underwater, or ground-based vehicles, smart city technology, smart manufacturing, visual processing, and 5G-AI integrated systems.
As part of the funding round’s closure, senior leaders from Renesas and GHOVC will join the EdgeCortix Board of Directors.
About EdgeCortix:
EdgeCortix, founded in 2019, is a fabless semiconductor company based in Japan, focused on energy-efficient AI processing. The company adopts a software-first approach and utilizes its patented “hardware and software co-exploration” system to design an artificial intelligence-specific runtime reconfigurable processor. EdgeCortix delivers software and hardware products to customers worldwide, aiming to disrupt the rapidly growing edge AI hardware space across various sectors, including defense, aerospace, smart cities, industry 4.0, autonomous vehicles, and robotics.
For more information, please visit www.edgecortix.com.