Most file analysis starts with the wrong success metric
Teams often start by asking whether the model can summarize or classify a file. Those are useful tests, but they are not the end goal. The real goal is whether the system helps a person understand the file quickly enough to make or support a business decision.
The source evidence should never disappear
The biggest risk in AI file analysis is separation between the answer and the proof. If a reviewer has to reopen the file and search manually to verify the result, the system has shifted the work instead of removing it.
Mixed file collections are where the product proves itself
The strongest test is not one clean PDF. It is a real working set of files: contracts, appendices, forms, spreadsheets, and emails. That is where buyers see whether the product can analyze files in a way that holds up in production.