Bengaluru-based CynLr secures ₹5.5 cr in seed funding from Speciale Invest, Growx Ventures, others

CynLr, a Bengaluru-based robotics deeptech startup has secured ₹5.5 crore in a seed funding round from Speciale Invest, Arali Ventures, Growx ventures, CIIE Initiatives and Vijay Kedia.

The startup will use the infuse capital towards research and development as well as to drive adoption of the product.

Vishesh Rajaram, managing partner from Speciale Invest said, “We believe Vyuti is poised to become the brain and eye for every robotic hand, which would allow it to pick, orient and place items as reliably as humans, a development that could lead to the automation of all warehouse and manufacturing line jobs on earth.”

CynLr was founded by Gokul NA, and Nikhil Ramaswamy in 2015. The platform works toward automating the manual labour involved in manufacturing processes.

It is building a universal machine-vision enabled robot platform that can sense the clutter of the real-world and manipulate objects as well as humans do.

Rajiv Raghunandan, managing partner, Arali Ventures said, “We believe that CynLr’s approach of bringing together machine vision and AI will significantly enhance object intelligence for industrial robots, thus paving the way for greater penetration of robotics application across various industry segments.”

According to the company, it has, now, prove the intellectual property development and is aiming to productise its technology. The technology is using a multi-dimensional segregation approach along with coordinated and adaptive acquisition.

This has been enabled by an integrated eye-brain platform, and deep-neural network models reinforced with motion feedback.

While, the CynLr platform claims to accurately Pick and accurately Place even complex geometry objects, even when presented in a random bin with occlusions and entanglements.

Practically, the company’s robot can automate the physical labour with its proprietary vision hardware which is built for object manipulation.

The founders say that the ability of robots to understand the objects especially in clutter and randomness, to grasp and manipulate with accuracy has been an elusive unsolved problem in robotics till date.


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