Your Django App Has Years of Data. Here's How to Make AI Agents Actually Use It.

The Problem Every Django Developer Knows You have a Django app with years of data — products, articles, orders, users. Your users type natural language queries into a search box and get either nothing or keyword-matched garbage. Worse: you want to connect an AI agent that can answer questions about this data. But everything is locked inside relational tables. To feed it to an LLM, you either dump the database, write custom ETL pipelines, or stand up a separate vector store and manually keep i...