SilaiSathi: An Offline-First AI Workstation for Independent Tailors

A developer released SilaiSathi, an offline-first workstation for independent tailors and small tailoring businesses that manages customer measurements, order tracking, bookkeeping and local data storage, with optional AI workflows. Built with Python, Streamlit, SQLite and Pydantic, the open-source project supports local model integration via Ollama and the Gemini API, and includes work related to Gemma and AST integration linked to Graphify. The developer positions the tool as a demonstration of how open-weight models and local inference can make useful software more accessible to small businesses.

'SilaiSathi' is an 'offline-first' digital workstation designed to help independent tailors and small-scale tailoring businesses organize their daily operations. It focuses on managing customer measurements, tracking tailoring orders, handling business bookkeeping, local data storage, and AI-powered workflows optional . Repository: https://github.com/dikshant363/silaisathi https://github.com/dikshant363/silaisathi A public live demo is available here: https://silaisathi.streamlit.app/ https://silaisathi.streamlit.app/ This project utilizes Python, Streamlit, SQLite, and Pydantic. It also includes support for local model integration via Ollama and the Gemini API. The codebase features work related to Gemma, as well as AST Abstract Syntax Tree integration linked to Graphify. Open-source software and open-weight models provide developers with greater control over model selection, local inference, transparency, and costs. 'SilaiSathi' demonstrates how these advantages can be leveraged to make useful digital tools more accessible to small businesses.