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Blumind, a pioneering developer of ultra-low-power analog AI chips for edge computing, announced the successful closing of a $20M CAD Series A funding round.
The investment is co-led by Cycle Capital and BDC Capital, with existing investors including Fusion Fund, Two Small Fish Ventures and Real Ventures joining the round. The company is maintaining the round open as it engages in active discussions with strategic investors.
This significant investment will enable Blumind to accelerate the development and commercialization of AMPL -- its groundbreaking analog AI technology -- designed to dramatically reduce power consumption and latency for always-on AI applications. Blumind’s innovative approach to AI processing offers a paradigm shift from traditional digital methods, enabling highly efficient and performant AI. This technology is crucial for applications where power efficiency and real-time processing are paramount.
"Blumind’s patented approach using analog AI will not only revolutionize edge computing but also help solve the growing energy demand imposed by the adoption of AI. We are enthusiastic to support the team, as we believe their highly differentiated technology will play a critical role in the future of AI," said Andrée-Lise Méthot, Founder and Managing Partner at Cycle Capital.
Shane Wall, Partner at Fusion Fund, added: “Physical AI use-cases are emerging in diverse segments such as robotics, smart mobility, medical and AIoT. Blumind’s low-power, low-latency and low-cost semiconductors will be a critical ingredient.”
"This funding is a major milestone for Blumind and a testament to the transformative potential of our analog AI technology," said Niraj Mathur, CEO and Co-Founder of Blumind. "We are thrilled to partner with investors who share our vision of bringing efficient and powerful AI to the edge. This investment will allow Blumind to rapidly scale our operations and bring our solutions to market, empowering a new era of intelligent devices."
Blumind plans to use the Series A funding to:
* Expand its engineering and development teams to commercialize its first-generation AI processor for processing real-time sensor data.
* Accelerate the design and production of its next-generation analog AI chips for vision and large language model inferencing.
* Support existing tier 1 lead customers and establish strategic partnerships with key industry players.