# Intelligent document processing (IDP)

> Intelligent document processing uses OCR and AI models to read documents such as invoices, contracts and forms, extract the fields you need, check them and post them into your systems.

- Page: https://methodcrew.com/glossary/intelligent-document-processing
- Last updated: 2026-10-28
- Publisher: [The Method Crew](https://methodcrew.com/)
- Also known as: document AI

## How it works

An IDP pipeline runs the same stages for every document:

1. Intake from an inbox, upload folder, scanner or API.
2. OCR or a vision model turns each page into text with its layout.
3. Classification decides what the document is: invoice, purchase order, W-9, lease.
4. Extraction pulls the fields (supplier, dates, line items, totals) with a confidence score for each.
5. Validation checks them against rules and your records: totals add up, the PO exists, the supplier is approved.
6. Low-confidence or failed items go to a person, and the rest post to the ERP, accounting system or CRM.

Managed services such as [Azure Document Intelligence](https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/overview), Amazon Textract and Google Document AI handle common document types well. General vision models from OpenAI, Anthropic and Google read messy layouts that older template-based tools could not. A typical build uses both.

## How businesses use it

Accounts payable is the usual first project, because invoices arrive in volume and errors are easy to count. Other common uses are contract intake for legal teams, claims and policy documents in insurance, onboarding forms in healthcare and financial services, and delivery notes in logistics. See the [invoice processing pipeline](https://methodcrew.com/blueprints/invoice-processing-pipeline) and [contract review assistant](https://methodcrew.com/blueprints/contract-review-assistant) blueprints for two worked designs.

Our [IDP builds](https://methodcrew.com/services/intelligent-document-processing) run $12,000 to $40,000. OCR and extraction services charge per page, and those fees are billed separately at cost.

## Where it goes wrong

Accuracy on a vendor demo says little about your documents. Test on 100 to 200 of your own, including the worst scans and the odd suppliers, before you commit.

The second failure is skipping validation. A model can read a total correctly and still post it against the wrong supplier. Rules and record matching catch what extraction misses, and [human review](https://methodcrew.com/glossary/human-in-the-loop) handles the rest.

IDP is the wrong tool when documents already arrive as structured data, such as EDI or XML e-invoices. Parse those directly. It also rarely pays back at low volume: under about 100 documents a month, a person with a checklist is cheaper.

## Example (hypothetical)

Hypothetical: a building supplies distributor receives 3,000 supplier invoices a month as PDFs in a shared inbox. The pipeline extracts header and line items, matches each invoice to its purchase order in NetSuite, queues clean matches for approval and sends mismatches to an AP clerk with the discrepancy marked.

## Related terms

- [Human-in-the-loop (HITL)](https://methodcrew.com/glossary/human-in-the-loop): Human-in-the-loop is a workflow design where a person reviews, corrects or approves an AI system's output at set points before it reaches a customer or a system of record.
- [Large language model (LLM)](https://methodcrew.com/glossary/large-language-model): A large language model is a neural network trained on huge volumes of text to predict the next token, which lets it write, summarize, classify and answer questions.
- [n8n](https://methodcrew.com/glossary/n8n): n8n is a workflow automation platform, self-hosted or cloud, that connects apps and APIs in visual workflows and supports custom code and AI agent steps.
- [AI hallucination](https://methodcrew.com/glossary/ai-hallucination): An AI hallucination is output from a language model that is fluent and confident but false, such as an invented citation, policy, figure or product detail.
- [AI guardrails](https://methodcrew.com/glossary/ai-guardrails): AI guardrails are checks placed around a language model that block, rewrite or escalate inputs and outputs that break your rules on safety, accuracy, privacy or scope.

## Services where this matters

- [Intelligent document processing](https://methodcrew.com/services/intelligent-document-processing): Invoices, contracts and forms turned into clean, checked data. $12,000 to $40,000 per project.
- [Business process automation](https://methodcrew.com/services/business-process-automation): One cross-team process, such as client onboarding, rebuilt so the hand-offs run on their own. $5,000 to $40,000 per project.
- [AI automation](https://methodcrew.com/services/ai-automation): Workflows where a language model reads and sorts, and your existing systems do the rest. $4,000 to $35,000 per project.

## Articles that use this term

- [How to measure the ROI of AI automation, running costs included](https://methodcrew.com/insights/measure-ai-automation-roi)

Full glossary: https://methodcrew.com/glossary