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@article{175164,
        author = {Nasim Khan and Diwakar Shukla and Karan Rathod and Ashish Yadav and Deepa Athawale},
        title = {AI Integration in Multi Model Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {2032-2037},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175164},
        abstract = {The Advanced AI Assistant is a multi-modal artificial intelligence system designed to process and extract insights from documents, images, and structured data using cutting-edge technologies like BLIP, PyTesseract, Streamlit, and document parsers. The system integrates Optical Character Recognition (OCR), Natural Language Processing (NLP), and AI-driven contextual analysis to enable accurate text extraction, document summarization, and intelligent responses. Unlike conventional AI assistants limited to predefined commands, this model enhances user interaction by offering personalized AI capabilities and a context-aware processing pipeline.
This research presents the architecture, methodology, and experimental evaluation of the assistant, demonstrating its efficiency in handling PDFs, Word documents, Excel sheets, and image-based text extraction. Performance metrics, including OCR accuracy, response time, and contextual understanding, are analyzed against benchmark datasets such as ICDAR and DocVQA. The results show significant improvements in multi-modal data processing, automation, and adaptive learning. While challenges such as high computational demand and complex handwriting recognition exist, future enhancements will focus on real-time voice interactions, multilingual support, and industry-specific applications. This work establishes a strong foundation for next-generation AI-driven document and image processing systems.},
        keywords = {Artificial Intelligence, Deep Learning, Ensemble Learning, Multi-Model System, Machine Learning, OCR MODEL.},
        month = {May},
        }