Intelligent document processing (IDP) is the use of artificial intelligence to automatically extract, classify and validate data from documents. It combines computer vision technologies (OCR), natural language processing and machine learning to read and interpret invoices, contracts, receipts, delivery notes and other business documents, regardless of format or layout.
In B2B companies, the volume of documents processed daily is significant: supplier invoices, purchase orders, delivery notes, contracts, certificates. Manually entering this data into systems is one of the most time-consuming, error-prone and least satisfying tasks for teams.
What intelligent document processing is
IDP goes far beyond simple digitization. While a traditional scanner creates an image of the document, IDP:
- Identifies the type of document (invoice, purchase order, contract, receipt).
- Extracts specific fields (supplier, tax ID, date, amounts, product lines, references).
- Validates the data against business rules and information in the systems (does the supplier exist? is the reference valid?).
- Enters the data into the destination system (ERP, invoicing system, database).
- Flags exceptions for human review only when necessary.
From traditional OCR to AI
| Criterion | Traditional OCR | AI-powered IDP |
|---|---|---|
| What it does | Converts image into text | Understands the meaning of the text |
| Accuracy | 85 to 92% (characters) | 95 to 99% (extracted fields) |
| Variable layouts | Fails with new layouts | Adapts to unfamiliar layouts |
| Configuration | Template per document type | Automatic learning |
| Maintenance | High (new template per supplier) | Low (the model generalizes) |
How AI-based extraction works
- Document receipt. The document arrives by email, upload or integration with a scanner.
- Pre-processing. Image quality improvement (rotation, contrast, noise removal) if needed.
- Advanced OCR. Converting the image into text with recognition of layout, tables and text blocks.
- Intelligent extraction. The AI model identifies and extracts the relevant fields based on the document type.
- Validation. The extracted data is validated against business rules and data in the company's systems.
- Integration. The validated data is entered into the destination system (ERP, accounting, document management).
Services such as Azure Document Intelligence offer pre-trained models for invoices, receipts and identity documents, with the option to train custom models for company-specific documents.
Types of documents that can be processed
- Supplier invoices: extraction of supplier, tax ID, date, total amount, VAT, line-item details (see article on invoicing).
- Purchase orders: product references, quantities, prices, delivery terms.
- Delivery notes: origin, destination, volumes, weight, shipping references.
- Contracts: dates, amounts, specific clauses, renewal conditions.
- Receipts and expense notes: amount, date, category, establishment's tax ID.
- Certificates: type, expiry date, issuing entity, certificate number.
Results and metrics
- 80 to 95% reduction in processing time per document.
- Extraction accuracy above 95% for well-scanned documents.
- Processing of 500 to 2,000 documents per hour (versus 15 to 30 manually).
- Positive ROI within 3 to 6 months for companies processing more than 200 documents per month.
Case study: an industrial company that processes 800 supplier invoices per month reduced processing time from 12 minutes to 45 seconds per invoice. The error rate fell from 4% to less than 0.5%. The investment was recovered in 4 months.
How to implement it
- Identify priority documents. Start with the document type that has the highest volume and highest manual processing cost.
- Gather samples. Compile 50 to 100 examples of each document type for training and testing.
- Implement and test. Configure the extraction, validate accuracy and fine-tune.
- Integrate with the systems. Connect the extraction to the ERP or destination system for automatic entry.
- Monitor and iterate. Track accuracy over time and adjust for new suppliers or formats.
At Engibots, we help companies evaluate and implement intelligent document processing solutions, integrated with existing systems, to drastically reduce manual data-entry work.