Deploying AI Models at the Edge chip platform enters volume production, targets computer vision applications chip platform enters volume production, targets computer vision applications has announced the volume production for its purpose-built software-centric machine learning system-on-chip (MLSoC) platform, which will be used to address deployment and scaling issues in computer vision applications.’s MLSoC will provide improved machine learning capabilities, allowing for fast design iteration in minutes.

The company claims the MLSoC performs 10x better per watt and offers enhanced user experience for enterprises looking to scale existing edge ecosystems.’s MLSoC platform offers users the ability to quickly deploy applications at the embedded edge for a faster time to market.

“We are excited to take our very first purpose-built software-centric MLSoC to volume production,” said Krishna Rangasayee, CEO and founder of “This first-time-right success was made possible by a great team, fantastic technology partnerships, and our investors. I would like to thank them all for believing in our mission.”

The MLSoC device has a quad-core Arm Cortex-A65 processor and a machine learning accelerator block that offers 50 TOPS of ML acceleration. The company primarily designed the MLSoC platform to accelerate computer vision applications and address ML computational requirements.

“We’ve seen over a dozen edge processing solutions, and have never seen anything approaching the performance and power efficiency of’s MLSoC platform,” said Karl Freund, founder and principal analyst at Cambrian-AI Research. “Their solution is an order of magnitude faster and more energy efficient.”’s MLSoC platform offers a variety of products including licensed software, an evaluation platform, an MLSoC device, and production boards in PCIe and dual M.2 form factors.’s  MLSoC evaluation board uses the MLSoC device to support high-performance and low-power edge machine learning applications. The MLSoC device is available in industrial and consumer temperature grades to support various applications, such as smart vision, robotics, industry 4.0, autonomous vehicles, drones and the government sector.

Currently, the company is shipping the MLSoC platform to select customers, but the company has a form for additional inquiries. recently raised an additional $30 million in funding to accelerate the development of its machine learning chip platform for edge AI deployments.

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