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๐ YouTube Description (SEO-Optimized) ๐ In this video, I build a full end-to-end AI Stock Analysis Bot using CrewAI, GPT-4, Streamlit, and real market data. This is not a toy project โ itโs a production-ready, multi-agent AI system that performs: โ Stock price performance analysis โ Advanced risk & volatility metrics (Sharpe, Sortino, Drawdown, CAGR) โ Fundamental analysis using real financial data โ Price anomaly detection using quantitative methods โ Buy / Hold / Sell signal generation โ Per-stock AI memory (long-term insights per ticker) โ Natural language Q&A with context awareness The system uses multiple AI agents (Stock Analyst, Risk Analyst, Fundamental Analyst, Anomaly Analyst) orchestrated via CrewAI, combined with quantitative finance logic and LLMs for explainability. ๐ง What Youโll Learn How to design a multi-agent AI system How to combine LLMs + quantitative finance How to build AI systems with memory Real-world agent orchestration patterns Using Streamlit to ship AI apps fast Avoiding hallucinations with data-grounded AI ๐ ๏ธ Tech Stack Used Python CrewAI (Agent orchestration) OpenAI GPT models Streamlit yFinance Pandas & NumPy Quantitative finance metrics Session-based memory design ๐ฏ Who This Video Is For AI / ML Engineers GenAI Developers Quant & Finance Engineers Data Scientists Anyone building real AI products, not demos โ ๏ธ Disclaimer: This project is for educational purposes only and not financial advice. #ArtificialIntelligence #StockMarket #GenerativeAI #MachineLearning #Python #CrewAI #AgenticAI #LLM #OpenAI #AIEngineering #MultiAgentSystems #QuantFinance #StockAnalysis #AlgorithmicTrading #FinTech #EquityResearch #Streamlit #DataScience #PythonProjects #BuildInPublic #AIProjects