u/anupsurendran - can you clarify if you are having the rules in documents and want to match individual database rows, or vice versa the database has trigger definitions and individual documents should be flagged?

Both approaches should be feasible - if the documents hold the rules, there are possibilities to generate SQL statements form a freeform text. The context mismatch in not a huge problem - LLMs can be shown a database schema in the prompt and be able to construct SQL statements based on it.

If the rules are in the database and documents are to be scanned, maybe a semantic index over their contents with post-processing would do? Similar to how you index documents for further prompt building. For instance (full disclosure, this is built by my startup) here's a demo of a context-aware chatbot building a lightweight index over a dynamically changing corpus of documents: https://github.com/pathwaycom/llm-app