Abstract: The textile industry faces significant challenges in managing and analyzing monthly bills and invoices. Traditional methods involve manual data entry into Excel spreadsheets, making it difficult to extract insights about sales trends, pending payments, customer patterns, and business performance. Sathya Tex Web Analytics addresses these challenges by providing a comprehensive web-based platform specifically designed for textile businesses to manage bills and gain actionable insights through data analytics. The system allows textile companies to upload their monthly bills in Excel format, automatically processes and stores the data in DuckDB for high-performance analytics, and provides an AI-powered chatbot that answers business questions in natural language. Users can ask questions like 'What is my total sales this month?' or 'Which customers have pending payments?' and receive instant answers with the underlying SQL queries. The platform features a React-based dashboard displaying key performance indicators such as total sales, profit margins, pending amounts, and customer-wise breakdowns. Built using React for the frontend interface, FastAPI for backend API services, PostgreSQL for metadata storage, and DuckDB for analytical queries, the system integrates Groq large language model through LangChain to convert natural language questions into SQL queries. The AI component automatically generates safe read-only queries, executes them against DuckDB, and presents results in conversational format. This eliminates the need for textile business owners to learn SQL or hire data analysts. By combining modern web technologies with AI-powered analytics, Sathya Tex Web Analytics transforms raw billing data into strategic business insights, enabling textile companies to make data-driven decisions and improve operational efficiency.

Keywords: Textile Analytics, Bill Management, AI Chatbot, Natural Language Queries, DuckDB, FastAPI, Business Intelligence

Downloads: | DOI: 10.17148/IARJSET.2026.13371