The SEC Retriever on LangChain makes it easy for developers to retrieve context from SEC Filings for their generative and conversational agents, overcoming challenges such as LLMs missing context due to rapid financial market changes, embedding infrastructure evolving rapidly, and financial documents being complex. The SEC Retriever is powered by Kay's data APIs and Cybersyn's data-as-a-service company delivering analytics-ready economic data on Snowflake Marketplace. Developers can easily retrieve context from SEC Filings using the KayAiRetriever in LangChain, which provides a straightforward installation process and leverages state-of-the-art embeddings and query understanding to capture nuance and improve retrieval accuracy. The system consists of three essential components: data, representation, and retrieval, with Kay providing high-quality data APIs, Cybersyn delivering analytics-ready economic data, and Snowflake ensuring secure access to the data. By using the SEC Retriever, developers can enable analysts, auditors, investors, executives, sales, and marketing teams to parse financial information in seconds, improving decision-making and reducing costs.