PriceOptima AI

AI-powered dynamic pricing system that predicts optimal product prices based on demand trends and market data.

Overview

PriceOptima uses machine learning to analyze demand patterns and recommend optimal pricing strategies.
The system combines a predictive model with a dashboard interface for visualization.

Features

• Demand prediction using machine learning
• Dynamic price optimization
• Data visualization dashboard
• Interactive frontend interface

System Architecture

flowchart TD
A[Dataset: Historical Pricing & Demand Data] --> B[Data Preprocessing]
B --> C[Machine Learning Model]
C --> D[Price Prediction Engine]
D --> E[Backend Logic]
E --> F[Frontend Dashboard]
F --> G[User / Business Decision Maker]

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Pricing Dashboard

Demand Prediction Graph

Project Workflow

1. Collect historical pricing and demand dataset
2. Perform data preprocessing and cleaning
3. Train machine learning model for demand prediction
4. Generate optimal pricing recommendations
5. Display insights through an interactive dashboard

Tech Stack

Python
Machine Learning
Jupyter Notebook
React.js
JavaScript
CSS

How It Works

1. Historical demand data is used to train a pricing model.
2. The model predicts optimal pricing for different demand levels.
3. Results are displayed through a dashboard and frontend interface.

Future Improvements

• Real-time pricing updates
• Integration with retail platforms
• Advanced AI models

Author

Sana Shaikh