Bangalore- AgTech start-up TartanSense, has rebranded as Niqo Robotics. The rebranding comes on the heels of the company launching their proprietary green on green AI spot spray robots in India. With a fleet size of 50, this will be the world’s largest commercial deployment of AI powered robotic sprayers. Niqo’s proprietary green on green tech leverages real time AI assisted computer vision. This is to selectively spray chemicals on plants resulting in up to 60% chemical and water savings.
Niqo Robotics seeks to challenge the status quo of conventional farming methods. It is pioneering an AI powered robotics revolution in agriculture. This revolutionary spirit of the company is strongly embodied in the new brand identity. The name Niqo is derived from the word “Nikolaos”, meaning Victory of the People. The victory flag in the logo is symbolic of the brand’s ambition to liberate the entire farming ecosystem. Niqo aims to do this through the scientific application of AI-powered robotics in all major farming activities like sowing, spraying, and harvesting.
Mission:
As Niqo Robotics, the company’s mission is to make AI powered agricultural robots reliable as well as accessible. Staying true to this mission, Niqo Robotics has built their proprietary green on green AI spot spray tech stack. This is to seamlessly integrate with existing agricultural sprayers in the market, making it truly accessible.
Speaking on the rebrand, Mr Jaisimha Rao, CEO and Founder Niqo Robotics said, “It has taken us many years of innovation, frugal engineering, and rigorous testing to cover the distance from lab to land. The rebrand couldn’t have come at a better time. As we get ready to launch the world’s largest fleet of green on green AI spot spray robots to market , we need a strong identity that can boldly carry us into this exciting future. The name Niqo represents our hunger to win in this challenging ecosystem of robotics and agriculture . We are especially proud that India is leading the way for commercialising AI powered spot spraying at scale”.
