AI research products often display citations, but a row of links at the bottom of an answer does not tell you how the answer was built. A citation can be relevant to the topic without supporting the sentence beside it. Several links can repeat the same underlying source. A model can also drop important uncertainty while turning notes into fluent prose.
The data model has to preserve more than URLs. It should preserve the path from the original question to research queries, retrieved material, evidence grouped by claim, and the final report. We call that path an evidence chain.
This article focuses on the database and pipeline boundaries that make such a chain reconstructable.
The common shortcut: one giant JSON result
The fastest implementation is usually a job table with an input question and one JSON column containing everything else. It works until the product needs to answer operational questions:
