In today’s B2B marketplace, retailers face major obstacles in product discovery, purchasing efficiency, and inventory management. Traditional buying patterns lead to repetitive purchases, missed seasonal opportunities, and limited market competitiveness. Retailers often struggle with vast product catalogs, lack timely insights from distributors, and mismanage inventory due to information gaps. These inefficiencies cause up to 73% lost revenue from missed cross-sell opportunities, with 28% of retailers showing highly repetitive buying habits. The proposed solution introduces an AI-powered personalisation system that transforms procurement. It begins with intelligent data analysis, examining purchase histories, seasonal demand, categories, and geographic context to build detailed retailer profiles. Using advanced recommendation algorithms—combining collaborative filtering and content-based methods—the system suggests relevant, innovative products. Recommendations are delivered in real-time through web and mobile apps with push notifications for high-demand items. A continuous learning loop improves accuracy over time based on retailer feedback, purchase outcomes, and evolving trends. Key features include cross-sell intelligence, which identifies complementary items to increase order values, and upsell opportunities, suggesting premium or bulk options to boost margins. The system is supported by a robust, scalable tech stack: React.js and React Native for the front end, Node.js with Express for the backend, PostgreSQL and MongoDB for data, Redis for caching, and TensorFlow/PyTorch for AI models. Cloud deployment via Docker and Kubernetes ensures 99.9% uptime and scalability. Implementation follows four stages: secure data integration, advanced data processing, model training and validation, and real-time deployment. The journey spans 12–16 weeks, enabling smooth rollout and rapid adoption. The impact is transformative: retailers save 60% in discovery time and raise order values by 35%; distributors increase sales velocity by 45%; and platforms achieve 70% engagement growth. Research validation from MIT and Carnegie Mellon, plus real-world benchmarks from Amazon Business and Alibaba, reinforce its credibility. Overall, this AI-driven approach enhances retailer experience, strengthens distributor relationships, and fuels marketplace growth.

A comprehensive overview of our web application is available in the presentation deck, accessible via the Google Drive link provided below:https://drive.google.com/drive/folders/1cZhdPANiFOjaO-s9nDYTmbpJalaVBSE-?usp=drive_link