AI-Powered Voice Assistant for Business Automation

Anushka Upadhye, Sharvari Patil, Gayatri Sanap, Sanika Aher and Vandana Dixit

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2026, vol. 12, issue 3, 244-252

Abstract: The AI-Powered Voice Assistant for Business Automation is an intelligent enterprise automation platform designed to simplify business operations through voice interaction, artificial intelligence, and data-driven analytics. The system enables users to perform a variety of tasks, including email automation, financial data analysis, document retrieval, AI-based content generation, and social media management using natural voice or text commands. The frontend is developed using React, Axios, Chart.js, react-chartjs-2, and Framer Motion, while the backend is implemented using Node.js and Express, with additional Python services built using Flask or FastAPI. The system uses the browser’s Web Speech API, which leverages Google’s built-in speech recognition service for voice input and speech synthesis for audio responses. Google Gemini Flash models are integrated through the Google Gemini API for intelligent text generation and business content creation. Retrieval-Augmented Generation (RAG) is implemented using LangChain and ChromaDB to retrieve accurate information from uploaded documents. MongoDB is used for application data management, while PostgreSQL supports email automation workflows. Financial datasets in CSV format are processed using Pandas to generate summaries and visual insights. The proposed system demonstrates how voice interaction, artificial intelligence, document retrieval, and analytics can be integrated into a scalable platform to improve productivity and automate modern business processes.

Keywords: AI-Powered Voice Assistant; Natural Language Processing (NLP); Business Automation; Speech Recognition; Machine Learning; Task Automation; Enterprise Intelligence System (search for similar items in EconPapers)
Date: 2026
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT26123314
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DOI: 10.32628/CSEIT26123314

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