03 DOCUMENT WORKFLOW AUTOMATION · CASE STUDY
Automating document matching and Oracle ERP insertion.
Estimation AI identifies, matches, validates, and stores related estimation, mixing-sheet, and purchase-order PDFs within one controlled document-to-ERP workflow.
- Role
- Independent end-to-end engineering
- Environment
- Internal manufacturing workflow
- Stack
- Python · Flask · PDF · OCR · Oracle
3Related document types handled in one workflow
5Controlled stages from upload to Oracle storage
BatchSingle- and multi-page document processing
The workflow can reduce a several-minute manual process to seconds or a few minutes per batch, depending on document size and review needs. Formal production-wide savings have not been measured.
THE OPERATIONAL PROBLEM
Related PDFs had to be found, checked, and entered one by one.
Employees manually opened documents, searched for estimation numbers, matched related files, checked whether records already existed, and inserted each document into the ERP workflow.
The difficult part was preserving the relationship between files while preventing incomplete groups, incorrect identifiers, and duplicate Oracle records.
DOCUMENT-TO-ERP JOURNEY
Five controlled stages connect a PDF batch to Oracle.
Extraction accelerates document discovery; deterministic matching and validation decide what can move forward.
- 01
Upload
A batch can contain estimation, mixing-sheet, and purchase-order PDFs.
- 02
Extract
The system identifies document numbers across single- and multi-page files.
- 03
Match
Related estimation, mixing, and purchase-order documents are grouped.
- 04
Validate
Required relationships and existing Oracle records are checked before insertion.
- 05
Store
Approved document groups and their files are inserted into Oracle ERP.
SANITIZED MATCHING VIEW
One document group, visible before insertion.
The demonstration below uses fictional identifiers and contains no client documents or production data.
VALIDATION RESULTREADY FOR REVIEW
3 related documents matched- ✓ Identifiers extracted
- ✓ Required relationships found
- ✓ No duplicate record detected
- ✓ Oracle destination validated
Insertion remains a controlled action after validation. Demo values are intentionally fictional.
VALIDATION & SAFETY
Matching is useful only when the database operation is dependable.
01
Identifier validation
Extracted numbers are normalized and checked before they are used for grouping.
02
Relationship checks
The interface makes missing or unmatched documents visible before insertion.
03
Duplicate prevention
Existing Oracle records are checked so the same document is not inserted twice.
04
Controlled Oracle storage
Approved metadata and PDF files are written to the intended ERP document records.
MY OWNERSHIP
Independent engineering across processing, matching, interface, and Oracle integration.
I designed and developed the complete workflow independently, while operational requirements and validation scenarios came from domain users.
01Workflow discovery and document architecture
02PDF processing, OCR, and identifier extraction
03Multi-document matching and grouping logic
04Flask backend and validation interface
05Oracle BLOB insertion and duplicate prevention
06History features, deployment, and debugging
HONEST LIMITATIONS
Document quality and business rules still matter.
- OCR and identifier extraction can be affected by poor scans, unusual layouts, or damaged PDFs.
- Ambiguous and unmatched files require human review before insertion.
- Processing time depends on page count, file size, and the amount of validation required.
- Public visuals are sanitized; client identity, document content, and production records remain confidential.
Have a document-to-ERP workflow worth automating?
I’m available for selected PDF-processing, document-matching, and enterprise workflow projects.