MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202631017938 A) filed by Guru Nanak Institute Of Technology, Kolkata, West Bengal, on Feb. 18, for 'enterprise multichannel customer journey optimization platform using deep reinforcement learning.'
Inventor(s) include Ananjan Maiti; Nilanjana Adhikari; Dipankar Basu; and Monalisa Das.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "The offered solution is a personalising and optimising real-time multichannel customer journey, an intelligent and AI-driven enterprise system. By combining reinforced learning (Double Deep Q-Network), sequence modelling (bidirectional long short-term memory), and attention models, the invention adaptively learns the most effective marketing strategies applicable to the individual customer based on the ever-changing state at each of the digital points of contact. With more than 150 behavioural and contextual inputs, the proposed system chooses between 25 orchestrated marketing actions dynamically to maximize conversion, lifetime value, and engagement, minimize churn and lower operational expenses. The platform utilises prioritized experience replay, dimensionality reduction, and sophisticated reward modelling to provide robust and scalable learning. Real-world implementation with test and productive launches shows massive returns in conversion rate, customer value, and campaign efficiency. The architecture of the system permits enterprise-scale, sub second response times, complete channel alignment and stringent privacy protection bringing the proposed system in a position to be a building block technology of next generation digital commerce."
Disclaimer: Curated by HT Syndication.
