MGIT Placement Assistants
Year: 2025
Type: article
Abstract: The MGIT Placement Assistant is an AI-powered virtual assistant designed to streamline the placement process for engineering students at Mahatma Gandhi Institute of Technology (MGIT). Utilizing artificial intelligence and natural language processing (NLP), the chatbot provides instant responses to queries regarding job openings, recruitment schedules, company details, eligibility criteria, and interview preparation materials. By automating responses to frequently asked questions, the chatbot minimizes delays in information dissemination, ensuring real-time updates without manual intervention. It integrates with college databases and placement portals to deliver personalized assistance based on student profiles. Additionally, it supports multi-platform access through web and mobile interfaces, enhancing student engagement and accessibility. on the placement cell by handling repetitive queries. The MGIT Placement Chatbot modernizes the placement process, ensuring efficiency, transparency, and ease of access, making it a vital tool for successful campus recruitment. The MGIT Placement Assistant is a smart chatbot designed to empower engineering students with quick and reliable access to placement-related information. Using artificial intelligence and NLP, the assistant answers queries about job opportunities, recruiter details, eligibility, and interview tips. Personalized interactions based on academic records help students make informed decisions while preparing for interviews. The chatbot is available through both web and mobile platforms, offering constant support without the need for human mediation. This system enhances students’ confidence and preparedness while also supporting the placement team by automating routine tasks.
Authors: V Indra Kanti Rava, Bhookya Anurag, Shirisha.K, Mamatha, R. Mohan Krishna, Dr.K.Rajitha
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6912003115
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