Stock Market Trend Analysis and Report Generation Agent

Added Jun 2025 3 design docs

Financial analysts spend large parts of their week pulling stock data, spotting trends, and writing up findings, work that is essential, repetitive, and increasingly automatable. This project builds an agentic AI system that takes over the cycle from data retrieval to finished report. The intern constructs the system with Langchain orchestrating the workflow, LlamaIndex organizing and querying financial documents and data, and OpenAI models performing trend analysis and drafting narrative reports. Integrations with external market APIs supply real-time stock data, so analyses reflect current conditions rather than stale snapshots. A Flask backend, written in Python, exposes the agent's capabilities and manages scheduled and on-demand runs, feeding a customizable dashboard where financial analysts review generated trends, drill into the underlying data, and export reports. The project teaches the intern to combine live data feeds with retrieval-augmented reasoning and to make automated analysis trustworthy through grounding and transparency. Completing it demonstrates exactly the AI-plus-finance engineering profile that fintech firms and analytics teams are actively seeking.

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