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After 6 yrs R&D, young Kerala engineers ready to hit market with toddy tapping robot

From left : Charles Vijay V, Anup Sebastian and R Sreehari

A group of young engineers in Kerala is set to revolutionise the traditional toddy tapping with an ingenious robot that can swiftly tap toddy from coconut trees. Nearly after six years of research and development, their startup Nava Design & Innovation Pvt Ltd is finally all geared up to launch their flagship product Saper, a robot designed specifically for tapping coconut sap, in the commercial market.

Once installed atop a coconut tree, the Saper performs the duty of a traditional tapper without fail ensuring that fresh toddy is collected and transferred to the ground unit without any contamination. The startup has already acquired patents for their robot in 28 major coconut developing countries which constitutes 90 per cent of the global coconut market.

“We are thrilled that we are finally hitting the commercial market with our robot. It took six years of work to develop a commercially viable product. Our product will ease the workload of traditional tappers who risk their life climbing coconut trees each time to collect toddy,” said Nava Design Founder and CEO Charles Vijay V.

“Once the robot is installed atop a coconut tree by a tapper, he can avoid climbing the tree every time for collecting the toddy. Our robot reduces the burden of tree climbs from 270 times to just 2 times,” Charles told “Open Digest“.

The robot Saper developed by the youngsters

As per the details, the startup has developed a centralised closed collection technology through which a single tapper can handle toddy tapping coconut trees in hectares of land with much ease and increase productivity. The robot, which works on solar energy and is programmed with artificial intelligence, enhances productivity for tappers.  

With dwindling numbers of tappers, the startup expects Saper to be of much benefit to the toddy sector in Kerala. The robot also causes no damage to trees as it uses high precision sensors and machine learning to identify optimal spots for tapping.

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