Lincode, an AI visual inspection company, has closed another round of funding of an undisclosed amount. The investment has been raised from Accel, Tech Coast Angels, Nurture Ventures, Disruptors Capital and Arka Venture Labs.
Lincode enables manufacturers to identify surface defects, identify and measure individual components, and generate real-time data about products on the production line through its flagship industry 4.0 solution, the Lincode Visual Inspection System (LIVIS).
The automotive industry has shown an impressive adoption of advanced manufacturing technologies. Manufacturers are not hesitant to deploy technology or a solution that they know will bring them high Return on Investment (ROI), said Rajesh Iyengar, Founder and CEO, Lincode. “Our Artificial InteIligence (AI)-backed visual inspection solution has made inspection of production lines much more efficient than the traditional vision systems. The manufacturers have seen a drastic difference with our solution,” he added.
Shekhar Kirani from Accel said, “We are excited about how Lincode is taking industry 4.0 to the next level, leveraging AI/ Machine Learning (ML) to revolutionise precision manufacturing.” Quality inspection is a critical challenge faced by manufacturers across industries and Lincode has an amazing Internet Protocol (lP)/ Technology to address in multiple categories and markets, he added.
“We invested in Lincode because we believe it is the future as customers demand zero defects, ” said K C Chea of Tech Coast Angels, San Diego. The investor believes the company’s computer vision technology is promising for the automotive industry, and manufacturing in general. The solution will deliver higher quality products at a lower cost.
Yashwanth Hemraj, Founding Partner of Arka Venture Labs said, “Our investment in Lincode aligns with our vision of backing game-changing cross-border vertical solutions that are built with three main components - AI, workflow automation and datasets.”
The automotive industry is said to be making large investments in smart technologies such as AI, industrial internet of things (IIoT), automation, big data, 5G, etc, to streamline and scale up the automotive manufacturing process for higher efficiency and production capacity.
(with inputs from BL Intern Haripriya Sureban)