AI Number &
Character Reader (OCR)

Usage Context and Data Preparation

OCR turns text on tags, labels and documents into data for search or comparison. Serial numbers, lot numbers and dates have different formats and meanings. Identify the fields required rather than treating all extracted text as the same type of identifier.

Prepare actual document or label samples, languages, field locations and reference records for cross-checking. For ERP/WMS transfer, specify which fields require review before posting, especially similar-looking characters, leading zeros and date formats, so extracted data retains the meaning of the source.

OCR recognizes characters; field extraction identifies document numbers, lots or dates. Evaluate both separately. Complete recognized text can still populate wrong fields when layouts change or similar values occur together. Establish examples and rules for each document type.

Document images need sufficient sharpness, angle and light. Folds, stamps and faded print can obscure text. Test actual captured documents, including unreadable cases, not only clean original files. Do not invent unsupported content to complete an expected form.

Preserve field types and meanings. Identifiers with leading zeros belong in text fields; dates need known formats and calendars. Similar letters and digits need appropriate references. Structure checks can screen errors but do not justify unsupported automatic character replacement.

ERP/WMS integration needs document or transaction identity and duplicate handling. A repeated submission should distinguish correction from rereading, preserving source results and review reasons under the agreed scope. Successful extraction is not transaction approval or proof that a document is authentic.

Evaluate field accuracy and complete-document usability, emphasizing fields required before posting. Average character scores can hide consequential errors in identifiers or amounts. Uncertain fields need human review with controlled access to personal or confidential business information in documents.

Templates, reference matching and approval integration are proposals until scope and joint trials are confirmed. Extracted document text remains input data, not permission for the system to execute instructions or actions beyond the authorized purpose of the workflow.