diff --git a/README.md b/README.md
index 54b1db9..ee33aec 100644
--- a/README.md
+++ b/README.md
@@ -1,28 +1,31 @@
-AI Image Analyzer
+## Tensor Hub
 
-The AI Image Analyzer is a web application that allows users to upload an image and analyze it using the MobileNet model powered by TensorFlow.js. The application provides predictions about the image’s contents, displaying both the class name and the confidence score. Users can also download the analysis results.
+Tensor Hub is a versatile AI-powered web application that allows users to analyze data using various machine learning models powered by TensorFlow.js. The current version supports image analysis using the MobileNet model, but the app is designed to incorporate additional models in the future. Tensor Hub provides predictions with confidence scores and allows users to download the analysis results. It’s built using Next.js and Tailwind CSS for a fast, responsive front-end experience.
 
 Features
 
-    •	Upload an image file for analysis
-    •	Analyze the image using the MobileNet model
-    •	View detailed predictions with confidence percentages
-    •	Download the analysis results as a text file
-    •	Responsive design with full mobile support
-    •	Uses Next.js and Tailwind CSS for efficient and fast front-end development
+	•	Upload a file (e.g., images) for analysis
+	•	Analyze data using the MobileNet model
+	•	View detailed predictions with confidence percentages
+	•	Download the analysis results as a text file
+	•	Responsive design with full mobile and tablet support
+	•	Built with Next.js and Tailwind CSS for performance and scalability
+	•	Planned future support for all TensorFlow.js models (e.g., text, object detection)
 
 Demo
 
-Check out the live demo here:
+Check out the live demo here: https://nisalrenuja.github.io/tensor-hub/
 
 Table of Contents
 
-    •	Getting Started
-    •	Installation
-    •	Usage
-    •	Technologies Used
-    •	Contributing
-    •	License
+	•	Getting Started
+	•	Installation
+	•	Usage
+	•	Build for Production
+	•	Deploying
+	•	Technologies Used
+	•	Contributing
+	•	License
 
 Getting Started
 
@@ -32,75 +35,67 @@ Prerequisites
 
 Ensure you have the following installed on your system:
 
-    •	Node.js (v14 or higher)
-    •	npm or yarn
+	•	Node.js (v14 or higher)
+	•	npm or yarn
 
 Installation
 
-    1.	Clone the repository:
+1.	Clone the repository:
+git clone https://github.com/your-username/tensor-hub.git
 
-git clone https://github.com/nisalrenuja/tensor-hub.git
-
-    2.	Navigate into the project directory:
 
+2.	Navigate into the project directory:
 cd tensor-hub
 
-    3.	Install dependencies:
 
+3.	Install dependencies:
 npm install
+or, if you prefer yarn:
+yarn install
 
-or if you prefer yarn:
 
-yarn install
 
 Usage
 
-    1.	Run the development server:
-
+1.	Run the development server:
 npm run dev
-
 or
-
 yarn dev
 
-    2.	Open http://localhost:3000 in your browser to see the app in action.
 
+2.	Open http://localhost:3000 in your browser to see Tensor Hub in action.
 Build for Production
-
 To create an optimized production build, run:
-
 npm run build
-
 or
-
 yarn build
 
 The production-ready files will be output to the .next directory.
 
 Deploying
 
-You can easily deploy this app to platforms like Vercel or Netlify by following their documentation for deploying Next.js applications.
+You can easily deploy Tensor Hub to platforms like Vercel or Netlify by following their documentation for deploying Next.js applications.
 
 Technologies Used
 
-    •	Next.js - React framework for server-side rendering
-    •	Tailwind CSS - Utility-first CSS framework for styling
-    •	TensorFlow.js - Machine learning in the browser
-    •	MobileNet - Pre-trained image classification model
-    •	Lucide Icons - Simple and beautiful SVG icons
-    •	React - Front-end JavaScript library
+	•	Next.js - React framework for server-side rendering and static site generation
+	•	Tailwind CSS - Utility-first CSS framework for styling
+	•	TensorFlow.js - Machine learning in the browser
+	•	MobileNet - Pre-trained image classification model for analyzing images
+	•	Lucide Icons - Simple and beautiful SVG icons
+	•	React - Front-end JavaScript library
 
 Contributing
 
 If you’d like to contribute to this project, please follow the steps below:
 
-    1.	Fork the repository.
-    2.	Create a new branch for your feature/bugfix.
-    3.	Make your changes and test thoroughly.
-    4.	Submit a pull request explaining your changes.
+	1.	Fork the repository.
+	2.	Create a new branch for your feature/bugfix.
+	3.	Make your changes and test them thoroughly.
+	4.	Submit a pull request explaining your changes.
 
 License
 
 This project is licensed under the MIT License - see the LICENSE file for details.
 
-Feel free to modify this README.md file to match the specifics of your project, such as adding your own deployment links or any other project details. Let me know if you need further help!
+Feel free to modify the project details or deployment link when you’re ready to share it publicly. Let me know if you need any further changes or additions!