This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend
What I Built
I built Dukaandaar AI for my friend Suman Mandal, who works as an accountant handling inventory-related operations.
The idea started from seeing how much day-to-day business information can involve repetitive entries, calculations, inventory tracking, sales, purchases, and expenses.
I wanted to build something that could make these tasks easier and more natural to interact with.
Dukaandaar AI is an AI-powered business management application for small shops and businesses. It provides features for:
- 📦 Inventory management
- 🛒 Sales
- 📥 Purchases
- 💰 Expenses
- 📊 Business reports
- 📉 Losses and adjustments
- 🤖 Natural-language interaction with business data
- 🎙️ Voice-based interaction
For example, instead of manually searching through the application, a user can ask:
"How many units of this product are left?"
or:
"How much did I spend this month?"
The project started as something I wanted to build for one real person, and then I decided to stretch the idea into a more complete tool that could potentially be useful for other small businesses as well.
Demo
Code
Repository: https://github.com/devrittik/dukaandaar-ai
Live
URL: https://dukaandaar-ai.vercel.app
How I Built It
Dukaandaar AI is built with:
- React
- Node.js
- Express
- MongoDB
- REST APIs
- AI/LLM integrations
- Local AI components
- Speech-to-text / voice interaction
- Authentication and application logic
A major design goal was to support both local/private and hosted deployments.
For users who want maximum privacy, the application can be run locally with local AI components, allowing business data to remain on their own machine.
For users who prefer convenience and remote access, the application can also be deployed as a hosted application.
The AI is not intended to be just a chatbot sitting beside the application. The goal is to make AI an actual interface for interacting with structured business information.
Why Does Open Innovation Matter?
For a small business application, privacy can be extremely important because inventory, sales, purchases, and financial information can be sensitive.
Open-source AI and local inference make it possible to build an AI-powered application where users can choose to keep their data and inference local instead of being completely dependent on a closed third-party API.
It also gives developers more control over the AI layer. Models and inference approaches can be changed or upgraded without having to redesign the entire application around a single proprietary provider.
For Dukaandaar AI, that flexibility is especially useful because the project supports both fully private/local usage and hosted usage.
My Agent Session
This project was not built using DevRelay, so I don't have an agent session to include.
Prize Categories
Best Use of ElevenLabs
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