edgetensor has developed a mass market affordable camera based AI and vision SDK that runs on low power off-the-shelf commodity edge devices and works with most cameras. The proprietary edge AI technology with software innovation performs computations locally by only sending event-driven information to the cloud and bypassing cloud computing roadblocks such as speed, latency, privacy, reliability and safety concerns.
In addition to the current complete Face Inference solution, the SDK can also be used for various camera based AI applications such human detection and pose tracking, vehicle detection and identification, and speech recognition. The SDK has applications in in-vehicle monitoring to save lives by preventing distracted driving, enhancing video security in public places as well as applications in robotics, smart cities, retail attribution, marketing, fintech, healthcare, and more. edgetensor’s state of the art AI and vision SDK provides a minimum of 6X reduction in cost or more on the edge, plus a 1000X in cloud savings.
Rajesh Narasimha and Soumitry J. Ray are the founders of edgetensor. Headquartered in Dallas, Texas, with a development centre in Bengaluru, the startup’s mission is to make state-of-the-art edge based AI affordable and accessible to the mass market.
“Edge computing is growing rapidly and with many large companies investing in low-power edge compute devices there is a need for software innovation to run AI algorithms that are compute, memory, and data intensive on off-the-shelf commodity devices in a scalable and affordable way, and we at edgetensor are committed to making this happen,” commented Rajesh Narasimha, CEO at edgetensor.
“We are excited to have SRI Capital as our lead investor since they bring a wealth of expertise in enterprise tech to help us scale the business” added Narasimha.
Narasimha and Ray have obtained their PhDs from the Georgia Institute of Technology and between them, share more than 75 patents and publications and over a decade of industry experience. Both were part of metaio, a German AR startup acquired by Apple in 2015. The extended team of edgetensor comprises computer vision and machine learning experts and software engineers that bring together experience in cross-platform and mobile development along with cloud backend expertise.
“Another important aspect of edge computing is the volume of data sent to the cloud, more so in case of video data from camera sensors, and the power consumed to process the data is high which is reflected in the cost of cloud services,” said CTO, Soumitry J. Ray. “Edge devices being inherently low powered alleviate these issues by crunching the data themselves and thus reduce the cloud footprint of AI algorithms.” he added.
In simple terms, an edge device can perform computations locally without sending data to the cloud for processing and bypassing cloud computing roadblocks such as speed, latency, privacy, reliability, and safety concerns. What sets edgetensor apart from its competition is its proprietary AI inference engine that uses deep-learning algorithms optimized for low-cost edge computing devices such as a smartphone that can process 30 to 40 frames per second by only sending event-driven information to the cloud. edgetensor’s solution works with a wide range of edge hardware devices and is compatible with most of the cameras.
Its SDK handles a number of functions, including, face tracking with occlusion reasoning, head-pose tracking and location, gaze direction and location, age and gender, face recognition, face identification/verification, and emotion recognition.
And beyond facial tracking, the SDK can also be used for human detection and pose tracking, vehicle detection and identification, and license plate recognition. This means the tech has applications in markets such as video security as well as applications in mobility, personalised robotics, smart cities, smart retail, and marketing.
Commenting on the announcement, Sashi Reddi, Founder and Managing Partner at SRI Capital said, “There are very few entrepreneurs globally who can match Rajesh and Soumitry in their expertise in AI and vision processing on the edge. We believe that edgetensor has the potential to be a serious player in this multi-billion-dollar market for affordable AI on low end edge devices.”
SRI Capital is an early-stage venture capital firm focused on funding innovative startups primarily in the US and in India. They have offices in Philadelphia, USA and Hyderabad, India. In the last five years, they have invested in over 30 startups, and will continue scouting innovative startups to fund, collaborate and support cross-border innovation between India and U.S.
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