How Is Disrupting The Embedded Edge Market

San Jose-headquartered is gearing up to disrupt the $40 billion embedded edge market. is the brainchild of Krishna Rangasayee, who has previously led the $25 billion+ worth semiconductor business at Xilinx. 

The launch of a new design centre in Bengaluru ties in with the two-year-old startup’s plan to grow beyond Silicon Valley and Serbia, and enable large scale deployment of machine learning.

“We are very excited to start our design centre in India. We have already attracted some of the best minds to lead our efforts in both hardware and software. We plan to scale our team for machine learning and all aspects of our overall solution. India is rich in the talent pool and capabilities, and we are looking for the best innovators to come join us in our journey,” said Rangasayee, founder and CEO, 


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Analytics India Magazine caught up with Rangasaye to understand what makes SiMa tick.


The embedded edge is a $1 trillion+ market. However, the technology is decades old and is long overdue for an overhaul to accommodate today’s computing capabilities needs while managing performance, cost, and power. SiMa brings years of experience in machine learning to scale the adoption of ML at the edge to help customers innovate and bring new capabilities to market.

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SiMa also enables high performance with low compute power, and has created disruptive ML solutions 30x better than alternatives. It currently works with market leaders in robotics, security, health, and autonomous systems. 

Rangasayee said as machine learning scales in both the cloud and the edge, a lot of attention is paid to performance but not enough on power dissipation. “For machine learning to scale in adoption at the edge, it is extremely critical that attention be paid not only to performance but also to power,” he said.

“We are one of the key innovators in delivering high-performance machine learning to the edge at the lowest power possible. We are one of the few companies conscious about power and offer an efficient, sustainable machine learning solution,” he added. 

SiMa brings together different backgrounds, and skillsets to build a highly complicated program that is primarily software-centric but weaves in deep expertise in ML, silicon, and systems in a purpose-built platform. 

Currently, SiMa has 60+ innovators across California, Eastern Europe and India. 

Green ML With Embedded Edge Market

SiMa’s capabilities are at least 20X better than competitors in terms of frames per second per watt. 

“We believe we are leading the industry and making it possible to deliver high-performance machine learning at the edge while simultaneously reducing the power consumption associated with this compute. Another key area of innovation is the ease-of-use focus we have from a software customer experience. The combination of the two innovations give us a great comfort advantage over alternatives,” he said.

The embedded edge market today is serviced by classic system-on-chip companies. The pandemic has accelerated the need for a broad-scale adoption of machine learning to meet the rising demands of compute performance and cost. 

“We believe the incumbent solution providers are struggling to deliver to market needs from the machine learning perspective. We also believe that pure-play, mission-running accelerators alone are not going to meet the system needs of the embedded edge market,” he said.

To address this, SiMa is building a purpose-built machine learning SOC platform to meet the market’s needs and solve critical customer problems. “We believe we are spearheading the effort to disrupt a massively large market,” he said. 

SiMa sees immense opportunity in the area of computer vision. Their work is focused on applications in smart vision, robotics, drones, and autonomous systems. 

“We have taken an approach to innovate where it matters to our customers and partner with industry leaders to leverage their strengths in other areas,” said Rangasayee. We have key technology partnerships with Arm, Synopsys, and TSMC and are leveraging their capabilities to build the overall software stack and hardware MLSoC solution.

“Over the past two years, we have gone from a concept to being focused on delivering production requirements for our customers on both software and hardware,” he said. In 2021, SiMa aims to bring the easy to use, highly deployable technology to production, and infuse intelligence in its products. 

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Srishti Deoras
Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.

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