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@article{180146,
        author = {Yashraj Rai and Neha Bharadwaj},
        title = {An AI-Powered Automated Calling System for Small Businesses},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {970-973},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180146},
        abstract = {Small and medium-sized businesses (SMBs) often face communication challenges due to limited resources, hindering effective customer outreach. This paper presents an AI-powered automated calling system designed for SMBs, enabling both bulk and targeted calls. The system uses a React/TypeScript frontend (with Material-UI, Framer Motion) and a Python/Flask backend integrated with the Twilio Voice API for AI-driven telephony (STT, TTS, basic NLP). Key features include CSV-based bulk calling, individual call initiation, real-time status updates, and secure API interactions via CORS and environment variables. The architecture follows a standard SPA-REST API pattern. This paper evaluates the technical feasibility and suitability of this stack for SMBs, analyzing benefits like efficiency gains and cost savings, alongside limitations such as regulatory compliance (TCPA, GDPR), AI accuracy, and potential misuse. Future enhancements, including CRM integration and advanced AI, are discussed.},
        keywords = {AI, Automated Calling, Conversational AI, Flask, GDPR, React, Small Business, TCPA, Twilio, TypeScript.},
        month = {June},
        }