Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{185287,
        author = {Rushikesh Bhabad and Ashish Vishwakarma and Sushil Salunke and Sanket Kele and Sagar Erande and Sandeep R. Jadhav},
        title = {Placer-Ai:-Placement and Internship Agent with Contextual Event-Driven Retrieval and Artificial Intelligence},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {1171-1179},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185287},
        abstract = {The rapid evolution of academic and corporate ecosystems demands an intelligent, real-time platform to optimize student placements and internships. This research presents an AI agent-powered platform that seamlessly integrates Retrieval-Augmented Generation (RAG), event-driven architectures, and multi-database persistence to provide accurate, real-time updates for academic workflows. The system enables dynamic interaction between students, colleges, and recruiters, ensuring timely notifications, personalized recommendations, and efficient tracking of placement processes. By leveraging multiple data sources, the platform ensures high reliability and scalability, addressing challenges such as data heterogeneity, latency, and privacy. Experimental evaluation demonstrates enhanced workflow efficiency, reduced response times, and improved user engagement. This work contributes a novel approach to intelligent academic platforms, bridging the gap between AI-driven automation and real-time operational requirements.},
        keywords = {},
        month = {November},
        }