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  Some organizations have plenty of documents but no reliable way to identify their current version. That is a data governance problem before it is an AI problem. [url=https://ai-software-development.net]AI readiness assessment[/url] can frame the investigation, but it cannot replace ownership of the source material.
  
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  A prototype can prove that a model responds to sample inputs. An MVP has to fit a real workflow and expose enough behavior for product owners to judge it. Start with AI MVP engineering considerations when defining that boundary. The result still needs traceable inputs and a known owner. It also needs a fallback action.
  
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• Kommentar-Link Donnerstag, 15 Oktober 2026 20:05 gepostet von ML_Systems_CoM

  Document automation can fail before an LLM sees any text. Scanned pages may need OCR, tables can lose their relationships and repeated headers may pollute retrieval. An AI document processing design should preserve page references so every extracted answer can be traced to its source.
  
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