DEV Community

Aiman Fatima
Aiman Fatima

Posted on

HustleMate AI

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 💸

HustleMate AI 🚀 — Your AI-Powered Side-Hustle Assistant

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

What I Built

I built HustleMate AI, a web-based assistant designed to help freelancers, creators, and small-business owners manage everyday business tasks more efficiently.

Starting a side hustle means wearing many hats: marketer, salesperson, product manager, and business planner. Not everyone has the budget to pay for multiple tools or hire professionals for every task.

HustleMate AI brings several useful tools together in one simple dashboard:

  • ✍️ AI Content Writer — helps draft marketing content and social media posts.
  • 🛍️ Product Listing Assistant — helps create clear, engaging product descriptions.
  • 💰 Pricing Assistant — estimates service prices based on costs, time, and desired margins.
  • 📄 Proposal Generator — helps prepare initial proposals for potential clients.
  • ⚙️ AI Settings — allows users to configure their local AI model connection.

The goal is to reduce the time spent on repetitive business tasks so people can focus more on growing their side hustles.

Who is it for? Freelancers, online sellers, independent creators, and anyone building a small business.

What problem does it solve? It makes common business workflows easier to manage without needing a collection of separate tools.

Demo

🚀 Live Website: https://aiman00-coder.github.io/HustleMate-AI/

Explore the dashboard and try its available tools.

Code

💻 GitHub Repository: https://github.com/Aiman00-coder/HustleMate-AI

The project uses three core frontend files:

  • index.html — structures the dashboard and tool interfaces.
  • style.css — provides the styling and responsive layout.
  • script.js — handles interactions, pricing calculations, and AI requests.

The source code is available for people who want to explore, learn from, or contribute to the project.

How I Built It

I built HustleMate AI using HTML, CSS, and vanilla JavaScript to keep the application lightweight and easy to understand.

For local AI inference, the project is designed to connect to Ollama, which can run open-weight language models on a user's own machine. One example model configuration is qwen2.5:3b.

The intended architecture is straightforward:

  1. The frontend collects a user's task and relevant details.
  2. JavaScript sends an AI generation request to the configured Ollama endpoint.
  3. The model generates a draft or suggestion.
  4. The result is displayed in the dashboard for the user to review and edit.

The pricing assistant also provides a calculation-based workflow for estimating prices.

Because the frontend is deployed on GitHub Pages while Ollama normally runs locally, AI requests require a compatible local Ollama setup and appropriate browser-origin configuration. The hosted website does not itself host the AI model.

Why Does Open Innovation Matter?

Open innovation matters because powerful tools should not be limited to people and businesses that can afford expensive software subscriptions.

By building around open-source frontend technologies and supporting locally run open-weight models, HustleMate AI explores several benefits:

  • More control: Users can choose a compatible model and manage their own local setup.
  • Privacy-conscious AI: With a correctly configured local setup, prompts can be processed on the user's machine instead of being sent to a hosted AI provider.
  • Flexibility: Developers can experiment with different models and improve the workflows.
  • Accessibility: Freelancers and small businesses can explore AI-assisted work without needing to build an AI model from scratch.
  • Community collaboration: Other developers can suggest improvements, fix bugs, and add new features.

A closed API can be convenient, but it may tie an application to a particular provider, pricing model, or service. Open-weight models give developers another option: run inference locally and adapt the application around their needs.

For me, this project is a small example of how open innovation can make practical AI tools more approachable for people building something of their own.

Prize Categories

Please select the partner categories you are entering according to the official challenge rules. Only list categories for which the project meets the eligibility requirements.

Top comments (0)