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@article{188953,
        author = {Parigyan Gaur and Md Junaid Khan and Harsh Marwaha and Naman Purohit},
        title = {IRAA Intelligent Responsive Agentic Assistant},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {3996-3999},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188953},
        abstract = {The rapid advancement of Artificial Intelligence (AI) has led to the development of intelligent assistants capable of understanding and responding to human needs in real time. IRAA (Intelligent Responsive Agentic Assistant) is a desktop-based AI assistant designed to enhance productivity, automate repetitive tasks, and provide intelligent, context-aware responses through natural language interaction.
Unlike traditional assistants that rely heavily on cloud infrastructure or dedicated IoT hardware, IRAA operates entirely on a local machine (localhost) and is optimized for privacy, responsiveness, and ease of deployment. The system supports both voice and
text-based interaction and integrates intelligent task automation, real-time information retrieval, and conversational reasoning using GPT-based large language models.
The assistant follows an agentic architecture, where a central reasoning agent plans, decides, and executes actions across multiple integrated tools such as Gmail, Google Calendar, Spotify, Telegram, and
real-time information services. To improve usability, IRAA incorporates macOS Automator, enabling users to launch the entire system with a single click, without requiring manual terminal commands or development environments.
The modular backend architecture, combined with a lightweight frontend interface and local database storage, demonstrates how modern AI techniques can be effectively applied to build scalable, privacy-aware, and intelligent desktop assistants. This project contributes toward advancing research in agent-based AI systems and human-centered automation.
This project contributes toward bridging the gap between AI-driven automation and human-centered interaction, offering a scalable framework for future AI assistant development and research.},
        keywords = {Artificial Intelligence, Agentic Systems, Natural Language Processing, Desktop Assistant, Automation, Voice Interface, Localhost Execution, GPT Models.},
        month = {December},
        }