Pairwise Term Connection Explainer for Banking Vocabulary

Added Nov 2025 3 design docs

Finance students often know individual definitions but cannot connect them: they can define inflation and also interest rates, yet stumble when asked how one drives the other. A tool that takes any two or more banking terms and explains precisely how they relate fills a genuine gap in financial education. The intern builds this explainer in python. A user enters a set of terms, such as repo rate and mortgage pricing, and a langgraph workflow structures the analysis: the terms are interpreted, the type of relationship between them is identified, and an explanation is composed. Generative AI through openai models writes the final answer, describing the causal, definitional, or hierarchical link in plain language with a concrete example, while an agentic-ai layer coordinates the steps and handles cases where a relationship is indirect and needs an intermediate concept introduced. The tool outputs clean explanatory text a student can drop straight into study notes. The project is a focused introduction to AI-powered explanation: the intern practices structured prompting, workflow orchestration, and evaluating generated reasoning for correctness, all against a well-bounded educational use case.

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