The real problem starts after the PDF arrives

Businesses receive information in PDFs, scans, certificates and email attachments, but the useful business data must eventually reach spreadsheets, templates, CRM, ERP or another operational system.

The repetitive work is opening pages, locating fields, re-keying values, checking dates and references, creating output files and moving the result into another system. A useful automation handles this operating workflow, not only the text recognition step.

PDF receivedExtract approved fieldsValidate rulesHuman reviewStructured outputs

Tested Micro AI benchmark: 40 pages to 160 files

In a tested Micro AI workflow, one 40-page multi-record PDF generated 40 Excel files, 40 XML files, 40 CSV files and 40 JSON files: 160 structured files in total. The batch completed in under 10 minutes with 99.5% extraction accuracy under the tested document conditions.

1 PDF40 pages40 records4 formats each160 files
  • 40 pages × 4 formats = 160 files
  • 100 pages × 4 formats = 400 files
  • 500 pages × 4 formats = 2,000 files
  • 1,000 pages × 4 formats = 4,000 files

Why the larger examples are output counts, not promises

The 100-, 500- and 1,000-page figures are exact output-count calculations when four formats are required. Processing time and accuracy for larger batches still depend on document quality, field count, layout variation, validation rules and system capacity.

A production pilot should benchmark representative files instead of extending a small-batch timing result into an unsupported guarantee.

OCR alone is not a complete business workflow

OCR can recognise characters. An operational workflow must identify what the values mean, normalise them, apply business rules and decide what happens when information is incomplete or uncertain.

For example, AI-assisted extraction may identify an Analysis Date while a deterministic rule performs an approved expiry-date calculation. Interpretation stays flexible while fixed logic stays predictable and auditable.

Source valueAI-assisted interpretationApproved ruleValidated valueOutput template

What a controlled document workflow should include

CaptureSeparateExtractValidateReviewDeliver
  • Preserve the original source and create a processing reference
  • Separate records when one PDF contains multiple business documents
  • Extract only the fields approved for the workflow
  • Apply required-field, format, range, unit and cross-field checks
  • Route low-confidence and exceptional values to an authorised reviewer
  • Generate the approved Excel, XML, CSV, JSON or system-ready output
  • Keep the source, review decision and final output connected in an audit record

Where this creates practical value

  • Manufacturing: supplier certificates, inspection reports and quality records
  • Oil and gas: technical certificates, laboratory records and supplier documentation
  • Maritime and logistics: delivery orders, shipping records, vessel documents and invoices
  • Construction: site reports, material records and inspection forms
  • Finance and administration: invoices, purchase orders, statements and recurring reports

What to measure in the first pilot

The strongest automation case is not simply that AI can read a file. It is that the complete workflow reduces repetitive handling while keeping business controls visible.

  • Accuracy by business-critical field
  • Exception rate and reason for each exception
  • Elapsed processing time and staff handling time
  • Template and record-count parity across required outputs
  • Ability to trace every output back to the source