Regulatory Change Alert Builder with Retrieval-Based Context

Added Nov 2025 3 design docs

Compliance staff cannot read every regulatory update the moment it lands, so banks rely on alerting: short, targeted messages that tell the right people what changed and what to do. Producing those alerts quickly and accurately is a focused, high-value task for retrieval-grounded AI. The intern builds an alert builder as a streamlit application in python. Regulatory updates and reference materials are embedded and stored in a vector database, and when a user wants an alert on a topic, such as changes to customer verification requirements, a retrieval-augmented generation pipeline pulls the relevant updates and context. Generative AI then drafts the alert message: what changed, who is affected, and the recommended response, in a concise format suited to internal distribution. The interface lets users adjust scope and regenerate drafts, and because generation is grounded through RAG in retrieved regulatory content, alerts reflect the actual updates rather than model guesswork. The project teaches regulatory monitoring concepts, grounded drafting for high-stakes communication, and practical RAG pipeline construction, leaving the intern with a compact but convincing compliance-technology demonstration.

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