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iENSO announces the launch of an Ambarella-based platform ecosystem for embedded vision data applications

New product launch opens up new opportunities for powerful and cost-effective Edge AI

iENSO, a leading provider of embedded vision and Edge AI systems, announced today the launch of an Ambarella-based platform ecosystem for embedded vision applications. Ambarella, Inc. is an industry leader in AI vision processors for the Edge (NASDAQ: AMBA). The company’s solutions make cameras smarter by extracting valuable data from high-resolution video streams.

“Embedded vision is no longer just about the image. It’s about the data and the decisions the data enables,” says Mike Liwak, CPO. “This is why iENSO has been focused strategically on meeting customer needs at the crossroads of Embedded Vision, Edge AI and Cloud Connectivity. With this launch, we continue to invest in our commitment of putting best-in-class, power-efficient, and versatile processing power in the hands of our customers.”

The new ecosystem product will enable more powerful processing on the Edge, enabling iENSO’s clients to build in complex vision data processing and meet the ever increasing demands of different IoT markets. The ecosystem will include future-proofed turnkey products based on the Ambarella CV22 and CV25 that are tuned and tested with multiple different sensors and connectivity platforms. These advanced features make extremely powerful processing accessible to applications such as security, home automation, precision farming, automotive, robotics and wearable devices, and more.

“This is a game changer. We believe the current and future Ambarella roadmap elements will help companies to integrate powerful processing into their products,” says Vlad Kardashov, VP Engineering. “We look forward to helping our customers push the limits of Embedded Vision and Edge AI and extract the maximum value from vision data. We will support our customers through each step of getting their innovative products to market, from idea to manufacturing.”

SOURCE: iENSO

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