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github.com/onir/stock-analysis-agent

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Resume Bullets
  • Built a FastAPI-based stock analysis platform integrating financial APIs, valuation logic, and LLM query routing to generate natural-language equity research responses
  • Implemented multi-ticker comparison workflows using Python, structured financial data, and session memory to support follow-up stock analysis queries
  • Designed intent-based routing across valuation, financials, news, and peer comparison paths using FastAPI route handlers and structured LLM query dispatch
LinkedIn Post

I built an AI stock research tool that turns natural-language questions into valuation, financials, news, and peer comparison insights. The project uses FastAPI, financial data APIs, and LLM routing to understand what a user is asking, fetch the right market data, and generate a clear response. Biggest lesson: building useful AI products is less about the model and more about the data pipeline.

X Post

Built an AI stock analysis app. Ask "NVDA vs AMD" or "is AAPL undervalued?" and get valuation, news, and financial insights. FastAPI + financial APIs + LLM routing.

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