DukaanAI: A Local AI Business Assistant for Pakistan's Small Shops 🇵🇰
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle.
What I Built
Small shop owners deal with sales, inventory, daily expenses, and profit calculations every day. Many still manage these tasks manually or use disconnected tools, making it difficult to understand how their business is performing.
DukaanAI is an AI-assisted inventory and business management system built specifically for Pakistani Kiryana stores, general stores, and small retailers.
It brings everyday shop operations into one application:
- Inventory Management: Track products, stock levels, purchase costs, selling prices, and low-stock alerts.
- Point of Sale (POS): Process sales, validate available stock, calculate discounts, and print receipts.
- Expense Tracking: Record daily expenses such as shop rent, electricity bills, wages, and transportation.
- Business Analytics: View revenue, cost of goods sold, gross profit, operating expenses, and estimated net profit.
- CSV Exports: Export sales, expenses, and inventory records for further analysis.
- AI-Ready Architecture: Integrate an open-weight Gemma model through Ollama for local AI-powered business assistance.
The system uses Pakistani Rupees, supports locally relevant payment methods such as JazzCash and EasyPaisa, and includes realistic Pakistani retail demo data.
Who would pay for it?
Independent shopkeepers, Kiryana store owners, and small retailers who need an affordable alternative to complicated retail management software.
The business model could be a one-time setup fee or an affordable support and customization package. The goal is to make better business management accessible to shops that cannot justify expensive software subscriptions.
Demo
GitHub Repository: https://github.com/riazaslam029/DukaanAi
Video Demo: https://drive.google.com/file/d/1a42gF3KGqIwmlvL0sIVoH2X6CD3FU_6S/view?usp=sharing
The project includes sample retail products, sales history, and expenses so viewers can explore the main workflows.
Code
Explore the source code and run DukaanAI locally:
Repository: https://github.com/riazaslam029/DukaanAi
The project uses a React and TypeScript frontend, a Python FastAPI backend, and SQLite for local data storage.
How I Built It
I built DukaanAI using a full-stack architecture designed around practical retail workflows rather than relying on AI for every operation.
Technology stack:
- Frontend: React, TypeScript, Vite, Tailwind CSS, Recharts, and Lucide Icons
- Backend: Python, FastAPI, and Uvicorn
- Database: SQLite with SQLAlchemy
- Validation: Pydantic
- Open-weight AI: Google's Gemma through Ollama for local inference
One important design decision was separating deterministic business logic from AI-generated guidance.
Sales totals, stock deductions, expense records, and profit calculations are handled by application code. The AI integration is intended for natural-language assistance and business insights, where a language model can add value without becoming responsible for financial arithmetic.
The application also has an AI service interface that can detect a local Ollama instance and support a Gemma-based integration. The current repository documents the Gemma integration as a Phase 2 capability, so the AI functionality should be understood as a work in progress rather than a fully completed production feature.
Why Does Open Innovation Matter?
For a small shop, recurring AI API costs can make an otherwise affordable tool difficult to sustain. Sending business records to an external service can also raise privacy concerns.
Open-weight models such as Gemma offer a different approach.
With local inference through Ollama, DukaanAI can work toward three important goals:
1. Lower operating costs
Once the model is downloaded, local inference avoids per-request charges from a paid AI API. Hardware and electricity still have costs, but there is no requirement to pay for every model call.
2. Greater control over business data
A properly configured local deployment can keep sales, expenses, and inventory data on the shop owner's computer instead of sending that information to a third-party AI service.
3. Freedom to experiment and customize
An open-weight model gives developers more control over deployment and experimentation. It also makes it possible to explore different models and tailor the assistant to the language and workflows of Pakistani retailers.
Open innovation matters here because the people who could benefit from AI the most are not always the people who can afford expensive AI infrastructure.
I want DukaanAI to explore how local AI can make useful business software more accessible, affordable, and privacy-conscious.
Prize Categories
- Best Use of Gemma
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