CynLr, a robotics deep-tech startup building visual object intelligence for industrial robots, has raised a seed round of funding of ₹5.5 crore from two venture capital investors, Speciale Invest and Arali Ventures, the Centre for Incubation, Innovation and Entrepreneurship (CIIE) of IIM-Ahmedabad, and an individual investory, Dr Vijay Kedai.

The vision of the start-up, formerly known as Vyuti Systems Pvt Ltd, is to provide manufacturing companies looking to automate manual labour with a universal machine-vision enabled robot platform that can sense the clutter of the real-world and manipulate objects as well as humans do.

CynLr (pronounced “sign-lur”) was founded by N A Gokul and Nikhil Ramaswamy in 2015, who were earlier colleagues at the test and automation giant, National Instruments (NI). Gokul was a specialist in Machine Vision and Embedded Systems while Nikhil was a Key Accounts & Territory manager, with four years of experience each. They had together mapped out the glaring gaps in machine vision domain which till date has worked only for object identification but is heavily deficient for object manipulation applications.

Over the 4 years since inception, the founders have executed over 30 custom engineered, machine vision based robotic solutions for large manufacturing customers with hundred per cent attempt-to-success rate and have bootstrapped a sustainable business.

The founders are now aiming to productise their technology. CynLr plans to go-to-market with a single universal vision guided pick-orient-place robot platform capable of handling varied types of objects. Manufacturing customers can now rapidly deploy robots using the CynLr platform, without having to worry about custom designed fixtures and positioning systems which are currently mandatory for every robot deployment.

A press release from CynLr notes that despite years of advances in automation, manual labour still constitutes 31 per cent of time spent by world labour force as per a McKinsey study and is one of the hardest tasks to automate today. This is because of the sheer unpredictability in the way objects are present in the real world.

Industrial Robots today are blind and deploying them successfully requires expensive custom set-ups to structure the objects to be picked. So much that the costs incurred in deploying a robot today is several times the cost of purchasing the robot itself and it also takes 3-6 months to accomplish.

“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,” the release said.

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