Search for relevant document chunks based on a query. Under the hood, Captide’s RAG system uses a combination of LLMs and vector databases to find the most relevant chunks of text from corporate disclosures that are most relevant to the query. This endpoint returns chunks of text from corporate disclosures that are most relevant to the query, along with metadata about their source documents. This endpoint is useful for building search interfaces or retrieving specific content from documents.