AI Trend & Inventory Manager
ATIM is an intelligent inventory management system that combines real-time Google Trends analysis with AI-powered recommendations to optimize retail inventory decisions.
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The Problem
Retailers often struggle with stockouts of trending products due to delayed market awareness, overstocking of declining items, and reactive decision-making. Manual analysis of market trends is time-consuming and prone to error. ATIM addresses these challenges by providing real-time trend intelligence combined with AI-driven inventory recommendations.
Technical Stack
I built ATIM using Python (Flask) for the backend and Google Gemini AI for generating context-aware inventory strategies. Data processing is handled by pandas & NumPy, while the frontend utilizes Chart.js and Plotly for interactive visualizations.
AI-Powered Recommendations
The core of the system is the AI integration. Google Gemini generates specific reorder quantities, risk assessments for overstocking, and markdown recommendations for declining items.
Actionable Insights
- Low Stock Alerts: Immediate notifications with suggested reorder quantities.
- Priority Actions: A clear list of high-priority tasks to optimize inventory health.
- Comprehensive Analytics: Financial metrics, stock health monitoring, and category distribution.
Project Outcomes
ATIM successfully automates the inventory decision process, reducing the risk of both stockouts and overstocking. It demonstrates how integrating Real-Time Data with Generative AI can solve complex retail logistics problems.