Update README.md

README.md

@@ -1,19 +1,37 @@
 ---
-title: AgenticProcurement
-emoji: 🚀
-colorFrom: red
-colorTo: red
-sdk: docker
-app_port: 8501
-tags:
-- streamlit
+title: Agentic AI Procurement Demo
+emoji: 🤖
+colorFrom: blue
+colorTo: green
+sdk: streamlit
+sdk_version: 1.28.0
+app_file: app.py
 pinned: false
-short_description: Streamlit template space
+license: mit
 ---
 
-# Welcome to Streamlit!
+# Agentic AI Procurement Assistant Demo
 
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+This demo showcases an advanced Reinforcement Learning-powered Agentic AI system for automated procurement decision-making.
 
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+## Features
+
+- **Intelligent Decision Making**: Uses RL-trained models to make optimal procurement decisions
+- **Multi-Tool Integration**: Inventory checking, risk assessment, contract validation
+- **Real-time Analysis**: External data integration for supply chain disruptions
+- **Human-in-the-Loop**: Escalates complex scenarios to human experts
+- **Interactive Dashboard**: Beautiful Streamlit interface with real-time visualizations
+
+## How to Use
+
+1. Select a demo scenario from the sidebar
+2. Click "Execute Agent Decision" to see the AI in action
+3. View the agent's decision-making process and reasoning
+4. Explore the performance dashboard for model insights
+
+## Architecture
+
+- **RL Agent**: Custom Q-learning implementation for procurement optimization
+- **Tools**: Modular tools for inventory, risk, contracts, and execution
+- **Training Data**: 1000+ realistic procurement scenarios for model training
+- **UI**: Professional Streamlit interface with Plotly visualizations