DukaanSathi AI: Open-Weight AI for Small Indian Businesses

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle

What I Built

I built DukaanSathi AI, an AI marketing assistant designed for small Indian businesses, local shopkeepers, and online sellers.

Small businesses often need to write product descriptions, WhatsApp promotions, and customer replies but may not have a dedicated marketing team. Writing these messages repeatedly takes time, especially when they need content in different languages.

DukaanSathi AI aims to make this easier. Users can enter basic product details, choose the type of content they need, select a language such as English, Hindi, or Hinglish, and generate content they can review, edit, and copy.

The idea is to make AI-powered marketing assistance simple and accessible for businesses that want to spend less time writing and more time serving customers.

Demo

dukaansaathi-ai-gamma.vercel.app

The demo shows how a few product details can be turned into ready-to-edit marketing content.

Code

GitHub repository: https://github.com/Rakshit-Chauhan-byte/DukaanSaathi-AI

Built with Next.js, TypeScript, and Tailwind CSS.

How I Built It

I built DukaanSathi AI as a web application using Next.js, TypeScript, and Tailwind CSS.

The application collects product information and the user's preferences through a simple form. A server-side API route validates the input and sends a prompt to a hosted inference provider running an open-weight language model. The generated content is then displayed so the user can review, edit, and copy it.

I focused on keeping the MVP small and useful rather than adding unnecessary features. The model is responsible for the actual content generation, which makes AI a core part of the product rather than just an extra feature.

Why Does Open Innovation Matter?

For me, open innovation means having more flexibility in how AI-powered products are built and improved.

DukaanSathi AI uses an open-weight model so that I can experiment with different models, refine prompts for Indian business use cases, and explore better support for multilingual marketing content.

It also gives the project more flexibility as it grows. I can evaluate alternative models and inference providers instead of designing the entire application around a single proprietary model.

For this MVP, hosted inference made integration simpler and allowed me to focus on the user experience without managing model-serving infrastructure myself.

There is an important trade-off: this version uses hosted inference, so it requires an internet connection and sends generation requests to the selected provider. It is not a fully local or offline AI application.

My goal is to explore how open-weight AI can make practical, affordable tools more accessible to small businesses.

What's Next?

I want to test DukaanSathi AI with more small business owners, understand which generated content is genuinely useful to them, and improve the results based on their feedback.

This project has been an opportunity to explore how open-weight AI can be used to solve a specific, everyday problem rather than building another general-purpose chatbot.

Thanks for checking out DukaanSathi AI!