Smart Multiagent Shopping System
Prof. Samita Patil, Akshay Sonawane, Aaditya Revandkar · International Journal of Advanced Research in Science Communication and Technology · 2025
The Smart Multiagent Shopping System is an efficient tool that acts as a sophisticated web application designed to significantly improve user interface experience during the shopping visit by bringing into combination through the single architecture APIs from leading online e-commerce platforms like Amazon, Flipkart, Myntra, and Meesho. The system is among the most modern interfaces since it easily gathers and compares the details of products at least in terms of price and availability, and eventually features. This also enables the system to recommend the products to the user, which seems helpful as feedback for earlier searches throughout its true Personalized Recommendations. This becomes possible due to rewarding usefulness for general decision-making in terms of information flow and similar other criteria entailing to result accuracy, efficiency, and ease of operations. The work of this system is to facilitate a wishful query from a user to search his needs dynamically and deliver the most intelligent and automatic means to him. The paper addresses a number of significant challenges that exist in the unmediated arena of online shopping. What seems discouraging to many online shoppers is the constant and excessive purchase and the robust complexity in carriers and agents that provide a very competitive marketplace. The paper is on novel and requisite algorithms designed to assimilate API calls from various websites and conquer the obstacle of vigorous-looking, intelligent data representation. In the meantime, integrated prototypes are suggested to deliver sorted and appropriate outcomes while offering good performance. The research essentially tries connecting the ramifications of using multiagent applications in business practices to shopping paradise.