50x more energy efficient
establishing an AI infrastructure where all algorithms operate efficiently.
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Traditional AI solutions face challenges in AI inferencing and training, primarily due to energy sustainability concerns, carbon footprint, power penalties, cooling requirements, and form factors. By leveraging analog in-memory computing, we offer a more cost-effective alternative, significantly lowering operational costs.
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Ultra-low-power NPU enables compact, fanless design and reduces cooling costs for edge and data centers
Data privacy and security with on-device inferencing, reducing exposure to potential threats
Complete testing solutions to ensure the reliability and quality of the software.
optoML NPU paired with flexible configurations of ARM/RISC-V based CPU + GPU
High-value solution at a competitive cost point, maximizing ROI for AI deployments.
Design to PoC in Just 6 Months
FPGA-connected test and 130nm Analog compute
Achieved 95% accuracy with MNIST Model
Collaborating with TSMC for manufacturing next-generation chips
Use continuous time domain signals allowing more nuanced and energy-efficient computation.
We are confident that we will open strong networks to your company.
Founder and CEO
13 and growing
optoML Business
