Skip to content

Ananyasingh2002/InvestIQ

Repository files navigation

InvestIQ - AI-Powered Financial & Business Advisory Website for SMEs

InvestIQ

📍 Overview

InvestIQ is an advanced website offering personalised financial and business advice for Small and Medium Enterprises (SMES). By leveraging Gemini API 2.0 and machine learning, this platform assists SMES with loan predictions, business idea generation, and financial advice, enabling them to make informed decisions for growth.

Home Page

  • Description: The homepage introduces the core features of InvestIQ and provides easy navigation to the key services.

  • Screenshots: Home Page 1 :

    Home Page 1

    Home Page 2 :

    Home Page 2

Sign In and Available Services

  • Description: Users can securely sign in to access personalised services, including loan prediction, business idea generation, and financial advice.

  • Screenshots: Sign In Page :

    Sign In Available Services : Services

Loan Prediction Service

  • Description: Predicts loan approval chances based on user-provided financial information.

  • Functionality:

    • Loan prediction based on financial details.
    • AI chat is available for additional queries and guidance.
  • Screenshots: Loan Form :

    Loan Form

Business Idea Generator

  • Description: Generates personalised business ideas based on user inputs, such as capital, location, and sector.

  • Functionality:

    • AI-driven business idea generation.
    • Chat interface for further exploration.
  • Screenshots: Business Idea Form :

    Business Form

Financial Advice Service

  • Description: Provides personalised financial advice for SMES based on the user’s business needs and economic status.

  • Functionality:

    • Custom financial advice based on user inputs.
    • AI-powered chat for more detailed guidance.
  • Screenshots: Financial Advice Form :

    Advice Form

Additional Features

  • Interactive User Interface:
    • Backend: Flask.
    • Frontend: HTML, CSS, JavaScript.
  • Online Accessibility:
    • Hosted on Render.

The platform provides a user-friendly interface, offering SMES essential tools and AI-driven insights for their business needs.


📍 Installation and Setup

Prerequisites

  • Python 3.x
  • Pip (Python package manager)
  • Gemini API Key 2.0 for accessing the generative AI functionality.

Installation Steps 🚀:

Follow these steps to set up and run the InvestIQ application on your local machine:

1. Clone the repository Open your terminal and run the following command to clone the project:

git clone https://github.com/Ananyasingh2002/InvestIQ.git
cd InvestIQ

2. Prepare the environment

Delete the existing .env file (if present):

rm .env

3. Open and run the Prediction.ipynb notebook in Jupyter or VS Code to ensure everything is functioning properly

Make sure all required packages used in the notebook are installed. You can install missing packages using:

pip install package_name

4. Set up API and Flask secret keys Open app.py and do the following:

Replace the placeholder for your API secret key appropriately:

app.secret_key = "your_flask_secret_key_here"

To generate a secure key, run:

python -c "import secrets; print(secrets.token_hex(16))"

5. Install dependencies Ensure Python 3 is installed, then install the necessary packages from requirements.txt:

pip install -r requirements.txt

6. Run the application Start the Flask server by running:

python app.py

7. Open the application in your browser

Go to:

http://127.0.0.1:5000

About

InvestIQ is a Flask-based web app that uses machine learning and the Gemini API to predict loan eligibility and offer tailored financial advice and business ideas. Users can interact through smart chat forms, get personalized insights, and explore startup opportunities based on their country, income, and capital investment plans.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors