TVS Motor Company has invested $3.85 million (Rs 27 crore) in Bangalore-based startup TagBox, a supply chain IIoT (Industrial Internet of Things) and Machine Learning platform as part of its Series A funding round. The round was entirely led by TVS Motor and its Singapore based Subsidiary, TVS Motor (Singapore) Pte.

Rajesh Narasimhan, board member of TVS Motor Company and CEO of TVS Motor (Singapore) said: “We evaluated many companies providing IoT solutions in the Supply Chain and logistics space and found TagBox’s product offerings and solutions to be an unique blend of IoT, machine learning and close-loop AI. Their ability to help organisations monitor, predict and prevent SKU health risk in the supply chain is a clear differentiator. We are happy to invest in and strategically partner TagBox as they continue to pursue bottomline impact for Fortune 1000 companies by improving their supply chain processes while leveraging them for our own group businesses. Our current investment in TagBox is part of the initial set of investments being made in strategically relevant digital startups.”

Adarsh Kumar, CEO, TagBox said: “Organisations across the globe are increasingly adopting IoT and machine learning solutions to improve their supply chains and operations. We are excited that TVS Motor’s worldwide operations and experiences will help make our product and value proposition stronger and highly differentiated. We have already delivered ROI from our IoT-based predictive insights solutions for leading retail, e-commerce, pharma, F&B, dairy and manufacturing companies in India and APAC. We believe it is now time to scale our product globally.”

The Series A funding will be used to strengthen TagBox’s product innovation and R&D capabilities while expanding its global footprint. The company will continue to invest in their BoxLens and AssetLens platforms and develop new predictive analytics and automation solutions to solve various customer use cases.

Tagbox is helping organisations make their supply chains more reliable with solutions that lie at the intersection of IoT-based monitoring, machine learning and automation. The company aims to cost-effectively and reliably tag any supply chain shipment or asset at the highest level of granularity, monitor its health real time and using predictive insights ensure that the products’ quality is not compromised.

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