---
title: "What is Intelligent Document Processing?"
description: "Intelligent document processing (IDP) uses AI to extract, classify, validate, and structure information from PDFs, images, emails, forms, and other structured, semi-structured, or unstructured documents. Its pipeline combines document ingestion and preprocessing with OCR, document classification, NLP, layout analysis, data validation, human review for uncertain results, and delivery into downstream systems such as ERP, CRM, or accounting software. The post explains how embeddings support classification, how continuous learning adapts models to new layouts and corrections, and how metrics such as accuracy, throughput, confidence scores, and model drift support optimization. IDP can reduce manual effort, improve accuracy, lower costs, scale document-heavy workflows, and supply structured data for analytics, automation, AI agents, and retrieval-augmented generation, while high document variability and edge cases still make human-in-the-loop review relevant."
---

# What is Intelligent Document Processing?

[Databricks](https://yomu.fyi/company/databricks) · Databricks Staff · Sep 18, 2026

**Type:** Explainer

## Summary

Intelligent document processing (IDP) uses AI to extract, classify, validate, and structure information from PDFs, images, emails, forms, and other structured, semi-structured, or unstructured documents. Its pipeline combines document ingestion and preprocessing with OCR, document classification, NLP, layout analysis, data validation, human review for uncertain results, and delivery into downstream systems such as ERP, CRM, or accounting software. The post explains how embeddings support classification, how continuous learning adapts models to new layouts and corrections, and how metrics such as accuracy, throughput, confidence scores, and model drift support optimization. IDP can reduce manual effort, improve accuracy, lower costs, scale document-heavy workflows, and supply structured data for analytics, automation, AI agents, and retrieval-augmented generation, while high document variability and edge cases still make human-in-the-loop review relevant.

## Context

IDP is presented as a way to turn document-heavy workflows into structured, usable data. The approach supports operational automation, analytics, AI agents, and retrieval-augmented generation while retaining review for uncertain or high-stakes results.

## Approach / What changed

The explicit pipeline ingests documents, preprocesses them, applies OCR, classifies document types, extracts fields with NLP and layout analysis, validates and normalizes the results, structures the data, and sends it to downstream business systems. Human reviewers handle low-confidence outputs, while model feedback, new documents, external information, and performance monitoring support continuous improvement.

## Takeaways

- IDP combines OCR, NLP, machine learning, computer vision, embeddings, and layout analysis to process both structured and unstructured documents.
- Validation can include rules, normalization, cross-checking, confidence checks, and human review when the system is uncertain.
- IDP metrics include processing time, accuracy, throughput, precision, recall, confidence scores, and model drift, helping identify bottlenecks and optimize workflows.

## FAQ

### What happens when IDP is uncertain about an extracted value?

The system flags uncertain results for human review. A reviewer can verify or correct the data before it is structured and routed to downstream systems.

### How does IDP improve as document formats change?

IDP systems learn from corrections, new documents, and changing layouts. Machine learning models adapt to these variations, which can reduce manual intervention and improve extraction accuracy over time.

### Can IDP eliminate manual data entry entirely?

The source says IDP can dramatically reduce manual data entry, often by 80–90%. Enterprise deployments generally retain human-in-the-loop review for edge cases, low-confidence extractions, and high-stakes decisions.

**Tags:** [Document AI](https://yomu.fyi/topic/document-ai), [Machine Learning](https://yomu.fyi/topic/machine-learning), [Retrieval-Augmented Generation](https://yomu.fyi/topic/retrieval-augmented-generation)

- Source: [Databricks](https://www.databricks.com/blog/intelligent-document-processing)
- Source URL: https://www.databricks.com/blog/intelligent-document-processing
- Ingested by Yomu: 2026-09-17T14:12:59.031Z

[Read original post](https://www.databricks.com/blog/intelligent-document-processing)