Enterprise RAG often fails before the model sees the context. Noisy scans, merged table cells, and engineering layouts can turn a precise document into a weak index.
OCR/RAG and hybrid document research show that parsing quality cascades into retrieval, ranking, and generation.
Knovium should profile the archive before a pilot: scan share, table complexity, OCR quality, page anchors, and citation stability.
The practical value of this article is that it turns a research topic into an implementation checklist. Before a pilot, the team can see which data is ready, which documents need preparation, where manual labeling is useful, and which risks should be closed before the model is connected.
It is important to separate source-supported facts from product conclusions. The sources describe methods, limits, and metrics; Knovium applies them to enterprise archives with access rights, scan quality, domain terms, response latency, and accountability for wrong conclusions.