Silent record loss in document extraction pipelines

this is an easy one to miss in document extraction pipeline: all ok until your row counts dont match. This is actually a common one, when you extract rows out of the documents for instance invoices or statements/reports , short files come back clean so the pipeline looks rigid but once big documents enter the extractor starts silently under-returning rows. precision stays high so every value is correct but a chunk of the records never do come back and youd see no errors or logs being raised just the row count is quietly low The missing records that look like the document simply had fewer rows so you usually only notice when a downstream total doesnt reconcile. the fix is a completeness check rather big model. chunk the document by section, then extract each chunk and reconcile expected vs returned records, use it to bound what the count should be and fail loud when it comes up short, either build that yourself or use parsers like llamaparse or others and make sure you hand back per field grounding you can reconcile against