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@article{196129,
        author = {Siddhesh Sawant and Janhavi Anjarlekar and Prakash Bhatt and Soham Dhekale and Dr.Dibyalekha Nayak and Mrs.Namrata Gotmare},
        title = {Synergi- MultiAgent Chat Assistant},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {2271-2277},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196129},
        abstract = {For the modern digital age, it is not unusual for people to use numerous online services, such as health management, financial management, and study assistance, often across various platforms. The project, titled “MultiAgent Chat Assistant,” attempts to bring together these disparate functions in the form of a single intelligent platform. The solution, as proposed, brings together the functions of various specialized artificial intelligence agents, such as the Health Bot, Finance Bot, and Study Bot, into the form of a single, cohesive web application. The solution’s structure allows for accurate intent classification, efficient agent matching, and communication through the use of a centralized orchestrator. The solution’s structure, as proposed, includes the use of Next.js, Express.js, and PostgreSQL, ensuring the application’s scalability, modular structure, and ease of use. Through the use of parallel processing, semantic understanding, and communication, the MultiAgent Chat Assistant is able to provide coherent, relevant, and contextual responses to the queries posed by the user. The project represents an important milestone in the development of intelligent, unified, and multi-domain chat assistants that may be able to provide improved user experience and efficiency in interactions.},
        keywords = {MultiAgent Chat Assistant, Agent Orchestration, LLM, Next.js, Express.js, PostgreSQL, Intent Routing, Domain-Specific Agents, Scalability, NLP.},
        month = {April},
        }