An AI-powered business assistant built for small businesses, homepreneurs, and social-commerce sellers.
This is my submission for the Hacktoberfest Open-Source AI Challenge — Week 2: Side Hustle.
🔗 Live Demo: https://dukaanpilot-ai.onrender.com
💻 GitHub Repository: https://github.com/tashu031/DukaanPilot-AI
💡 What I Built
Small business owners often manage orders, expenses, invoices, inventory, and customer payments manually. Keeping everything organized can become time-consuming, especially for people running a business alongside their studies or other work.
DukaanPilot AI is a business management platform designed to simplify these everyday operations. It brings essential business tools together in one dashboard and provides data-grounded AI assistance to help sellers understand their business performance.
The goal is simple: less paperwork, better visibility, and more time to grow your business.
✨ Key Features
📊 1. Financial Dashboard
- Track total revenue, recorded expenses, estimated profit, and pending payments.
- View revenue and expense trends.
- Identify low-stock products and business recommendations.
📦 2. Order Management
- Create and manage customer orders.
- Track order and payment statuses.
- Organize customer and product information in one place.
🧾 3. Invoice Management
- Generate invoices linked to customer orders.
- View invoice details, payment status, and due dates.
- Open print-friendly invoices and save them as PDFs.
💰 4. Expense Tracking
- Record business expenses by category.
- View spending breakdowns.
- Understand where business costs are concentrated.
🤖 5. AI Business Assistant
- Ask questions about top-selling products, revenue, expenses, pending orders, payments, and inventory.
- Get responses grounded in stored database records for supported business queries.
- Receive practical suggestions based on recorded business data.
📝 6. AI-Assisted Order Parsing
- Convert seller messages into structured order details.
- Extract information such as customer name, product, quantity, price, order status, and payment status.
- Use a deterministic rule-based fallback when local AI inference is unavailable.
📉 7. Inventory Monitoring
- Track stock quantities and safety thresholds.
- Identify products that need restocking.
⚙️ 8. Store Settings
- Manage business profile information and store preferences.
🛠️ Tech Stack
Frontend
- React 19
- TypeScript
- Vite
- Tailwind CSS v4
Backend
- Python
- FastAPI
- Pydantic
- SQLite
AI
- Gemma through Ollama for local inference
- Deterministic rule-based processing and business intelligence as a fallback
Deployment and Development
- Git and GitHub
- Render
- REST APIs
🏗️ How It Works
- Business owners record orders, expenses, and inventory information.
- The FastAPI backend processes requests and stores business data in SQLite.
- Analytics services calculate revenue, expenses, estimated profit, payment dues, and product performance from recorded records.
- The AI assistant uses deterministic database-grounded responses for supported queries and can use Gemma through Ollama when the local inference service is available.
- The React frontend presents the results through dashboards, management pages, and the AI assistant.
The focus is on making business information easier to access without requiring sellers to maintain multiple disconnected spreadsheets.
🎯 Who Can Benefit?
DukaanPilot AI is designed with these users in mind:
- Home-based business owners
- Handmade jewellery and craft sellers
- Instagram and social-commerce entrepreneurs
- Small boutique owners
- Students building a side hustle
- Micro-businesses that need a simpler way to manage daily operations
🚀 Try the Project
🌐 Live Application: https://dukaanpilot-ai.onrender.com
📂 Source Code: https://github.com/tashu031/DukaanPilot-AI
Explore the dashboard, review the available demo records, test order and invoice workflows, and ask the AI assistant questions about the recorded business data.
Note: The deployed application uses shared public demo data. Please do not enter private customer information or sensitive financial details. Gemma inference depends on local Ollama availability; the deterministic fallback supports the deployed demo.
🧠 What I Learned
Building DukaanPilot AI helped me work across frontend development, backend API design, database operations, business analytics, AI-assisted data extraction, and deployment.
It also reinforced an important lesson: AI-powered business tools should distinguish between verified database facts and generated suggestions. Financial figures should come from recorded data rather than invented estimates.
🔮 What's Next?
Some areas I would like to explore further include:
- User authentication and isolated business workspaces
- More robust invoice and payment workflows
- Improved order extraction and validation
- Additional analytics and business reports
- More flexible AI integrations and testing
🙌 Built for the Side Hustle Spirit
A side hustle should be about creating value—not spending all day managing paperwork.
With DukaanPilot AI, I wanted to build something practical that brings business operations and AI assistance closer together for small sellers.
If you explore the project, I would love to hear your feedback!
⭐ Check out the repository: https://github.com/tashu031/DukaanPilot-AI
🌐 Try the live demo: https://dukaanpilot-ai.onrender.com
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