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Deirdre24/StockSense-Africa

Domain:

socioeconomic

Record type:

software
Creator:
Dei
Host:
# 🌍 StockSense Africa **AI-powered Inventory & Procurement Intelligence for Small Retail Businesses in Africa** --- ## πŸ“Œ Overview StockSense Africa is a smart inventory management and procurement decision-support system designed for small and medium retail businesses. It helps shop owners: - Track stock levels in real-time - Identify products that need urgent reordering - Compare supplier prices - Understand revenue performance - Generate AI-powered procurement recommendations --- ## πŸš€ Key Features ### πŸ“Š Dashboard (Overview) - Revenue trends over time - Total units sold - Product performance breakdown - High-level business KPIs ### πŸ“¦ Inventory Intelligence - Stock health monitoring (Critical / Warning / Safe) - Days-of-stock estimation - Automatic reorder alerts - Product-level sales analysis ### πŸͺ Procurement Tracker - Supplier price comparison system - Best price identification - Add and manage suppliers dynamically ### πŸ€– AI Insights Engine - Autonomous procurement agent powered by LLMs - Generates actionable reorder decisions - Produces supplier-ready messages - Business health scoring --- ## 🧠 AI Agent Logic The system uses an AI agent that: 1. Reads inventory data 2. Classifies stock risk levels 3. Evaluates supplier options 4. Generates procurement actions 5. Outputs structured business recommendations --- ## πŸ–ΌοΈ Screenshots > Replace these placeholders with actual images from your app ### πŸ” Login Page ### πŸ“Š Dashboard Overview ### πŸ“¦ Inventory View ### πŸͺ Procurement Module ### πŸ€– AI Insights Page --- ## πŸ› οΈ Tech Stack - Python 🐍 - Streamlit - Pandas - Plotly - Groq LLM API - Python-dotenv --- ## πŸ“ Project Structure ``` StockSense-Africa/ β”‚ β”œβ”€β”€ app.py β”œβ”€β”€ agent.py β”œβ”€β”€ login.py β”œβ”€β”€ sample_data.csv β”œβ”€β”€ .env └── screenshots/ ```` --- ## 🎯 Problem It Solves Small retail businesses often: - Overstock slow-moving items - Run out of fast-moving stock - Lack data-driven procurement decisions - Have no visibility into supplier pricing effic …