Billing staff needed to turn inconsistent documents into records they could check and post. Muhammad built a processing workflow that combined extraction, validation and a review queue, with a separate path for statement reconciliation.
Scanned files and varying document formats made manual entry a repeated task. Extracting text alone would not establish whether the right fields were present or whether the result matched an existing record.
The workflow needed to distinguish information it could process from information requiring a person’s judgment. Reconciliation added another requirement: compare statement entries with the management system before final posting.
The document pipeline combined preprocessing, OCR, classification, extraction and validation, with processing stages running in parallel. Field-level confidence guided the review of uncertain extractions.
The reconciliation workflow compared carrier statements with AMS360 records and separated exact, partial and unmatched entries. That distinction gave staff a reviewable set of exceptions before the final posting step.
Project materials showing the workflows and interfaces described in this case. Interface examples use test data.
The application connected document intake to validation and review, then connected statement comparison to posting. It made exceptions part of the product workflow rather than assuming every extracted value was ready to use.
Document automation needs an owner for formats, validation rules and exception handling. A takeover should include representative documents, access controls and the review criteria used before posting. That operating knowledge matters as much as the OCR service or model behind the extraction.
Project contribution: Muhammad. The scope described above identifies the work behind this case.
Editorial review: Ego Eimi · Updated September 6, 2026 · About the team
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