Anuj K Chobe, Prajwa Matsagar, Vaishnavi Chaughule, Roshan Ostwal, Ranjana Dahake | International Journal of Software Computing and Testing | Vol 11, Issue 02 | pp. 10-17 | ISSN: 2456-2351
Abstract
The “SaaS Multi-Model Integration” paper addresses the challenges faced by students in accessing timely, personalized, and cost-effective academic assistance. Individual large language model chatbots excel in specific areas – academic reasoning, mathematical problem-solving, or general queries – but their fragmented nature forces students to subscribe to multiple services, leading to wasted time, money, and effort, particularly during urgent academic needs. This paper consolidates the strengths of widely used large language models into a single subscription service. Students can create one account, pay one fee, and access a suite of artificial intelligence tools for text generation, image creation, video and audio support, and more, eliminating the need for multiple platforms or subscriptions. Additionally, the “DocuTutor” feature offers personalized document tutoring, providing tailored explanations for dense academic texts or complex research papers. Unlike generic search engines, it breaks down intricate concepts and delivers context-specific guidance, empowering students and educators with clear, effective communication of complex material. This paper presents a groundbreaking platform that streamlines access to cutting-edge artificial intelligence technologies and revolutionizes the educational experience through innovative, user-focused features.
Artificial intelligence, SaaS, subscription model, LLMs, AI modeless
Keywords
Artificial intelligence, SaaS, Subscription Model, LLMs
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How to cite this article
@article{ChobeAK2025,
author = {Anuj K Chobe and Prajwa Matsagar and Vaishnavi Chaughule and Roshan Ostwal and Ranjana Dahake},
title = {SaaS Multi-Model Integration: A Comprehensive Student Companion},
journal = {International Journal of Software Computing and Testing},
year = {2025},
volume = {11},
number = {02},
pages = {10--17},
issn = {2456-2351},
url = {https://journalspub.com/publication/ijsct/article=21883}
}