ClustroAI, a leading innovator in edge AI technology, has successfully raised $12 million in Series A funding to accelerate AI deployment on local and edge devices. With total funding now reaching $15 million — including an earlier seed round backed by NVIDIA — this investment was led by Forum Ventures, with participation from MetaBlast, Metaverse Group, and other prominent investors. The capital will enable ClustroAI to expand its platform, allowing enterprises to run AI models on local devices and edge servers without relying on cloud infrastructure.
ClustroAI’s containerized architecture is designed to optimize AI workloads across a wide range of devices, from smartphones to industrial machines and autonomous systems. This technology eliminates the need for cloud-based data transfers, enabling applications such as large language models (LLMs), generative AI (AIGC), real-time speech translation, and data processing while enhancing security, reducing latency, and cutting cloud computing costs.
“Our strategic partnership with NVIDIA is redefining edge computing,” said Chris, Co-founder of ClustroAI. “ClustroAI’s protocol-based architecture enables dynamic compute resource scheduling, transforming GPUs, NPUs, and even sensors into autonomous decision-making nodes. From industrial machinery to smart terminals, we are making compute power available on demand.”
With this funding, ClustroAI is focusing on simplifying AI operations by developing tools that enable enterprises to update AI models effortlessly, much like mobile apps, ensuring stability and ease of deployment. The company is also building a distributed AI compute network by leveraging container orchestration to connect computing power across multiple devices, improving efficiency and resource allocation. Additionally, ClustroAI is expanding hardware compatibility by supporting FPGA, TPU, and NPU chipsets to drive AI adoption across industries, including smart factories, security systems, and autonomous vehicles.
ClustroAI envisions a future where AI is seamlessly integrated into everyday operations without dependence on cloud infrastructure. This funding milestone propels the company toward making edge AI scalable, secure, and cost-effective for enterprises worldwide.
