Gurgaon-based artificial intelligence start-up Staqu has joined hands with Tech Mahindra, UK. The association is focused on powering content distribution in the European market with relevant and contextual recommendations, whilst creating use-cases to usher in new monetisation opportunities.
The association follows Staqu’s win at the Tech Rocketship Award, 2017-18, which exposed it to UK’s world-leading growth ecosystem of VCs, advisors, customers and support networks, thus begetting opportunities to springboard its business internationally.
Enterprises in the European market are required to ethically leverage data and respect the privacy of users, following the General Data Protection Regulation. With Staqu’s proven expertise in cross-content recommendations, video and image analysis, Tech Mahindra would be able to offer its users relevant and contextual content, while completely abiding by the GDPR.
Commenting on the association, Manish Upadhyay, Head of Entertainment and Media, Tech Mahindra for UK, Ireland, and South Europe Market said, “Staqu is a fast-growing AI start-up with proven expertise in contextual and relevant content recommendations. The alliance with Tech Mahindra will help to fuel co-innovation for Media and Entertainment customers in the UK. Tech Mahindra and Staqu are building some use cases jointly to create new monetisation models for media and Entertainment industry in the UK.”
Atul Rai, Co-Founder & CEO of Staqu further added, “It is a great opportunity for us to partner with Tech Mahindra and introduce our AI-based cross-content recommendation engine in the European market. Today’s users are extremely cautious about their data privacy and require content distribution to be relevant and contextual. With previously proven expertise in the domain, we are glad to partner with Tech Mahindra and power content distribution via content recommendations that are contextual and relevant to the users.”
The innovation being brought together by Tech Mahindra and Staqu would understand the content consumption patterns, without obscurely mining data. Furthermore, by understanding the individual behaviour of users, the AI-powered recommendation engine would aid relevant and contextual content distribution, completely removing any scope for blind recommendations.