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Ingest-Time Fact Compilation for Cost-Efficient and Reliable Question Answering over Revised Corpora

arXiv · AI, language, vision and robotics · article · Aug 29, 2026 · UTC

Most agentic question answering (QA) systems do an important part of their semantic work at the worst possible time: every time someone asks a question. When a corpus contains revisions, drafts, revocations, deletions, and sources with different levels of authority, the model must reconstruct the governed current state on every read - then throw that work away and repeat it on the next query. This is a bit like a database that rebuilds a materialized view every time someone reads from it. We present ingest-time fact compilation, an architecture that performs this work when corpus data is inges

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