Document AI is a document understanding platform that takes unstructured data from documents and transforms it into structured data, making it easier to understand, analyze, and consume.

Document AI uses machine learning and Google Cloud to help you create scalable, end-to-end, cloud-based document processing applications.

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Documentation resources

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Resources

Explore self-paced training, use cases, reference architectures, and code samples with examples of how to use and connect Google Cloud services.

Training

Training and tutorials

Optical Character Recognition (OCR) with Document AI (Python)

This codelab will teach how to perform Optical Character Recognition using the Document AI Python Client Library. You will explore how to perform online and batch processing of documents with a PDF of the classic novel "Winnie the Pooh" by A.A. Milne.

Document AI

Training

Training and tutorials

Form Parsing with Document AI (Python)

In this codelab, you will learn how to use the Document AI Form Parser to parse a handwritten form with Python. We will use a simple medical intake form as an example, but this procedure will work with any generalized form.

Document AI

Training

Training and tutorials

Specialized Processors with Document AI (Python)

In this codelab, you will learn how to use Document AI Specialized Processors to classify and parse specialized documents with Python. We will use an invoice as an example, but this procedure will work with any specialized document supported by Document AI.

Document AI Procurement Lending Contract

Training

Training and tutorials

Document AI Workbench: Uptraining

In this lab, you will create an Invoice Parser processor, configure the processor for uptraining, label example documents, and uptrain the processor.

Document AI Workbench Uptraining

Training

Training and tutorials

In this lab, you will create a Custom Document Extraction processor, import a dataset, label example documents, and train the processor.

Document AI Workbench Custom

Training

Training and tutorials

Document AI Warehouse

In this lab, you will learn how to ingest, process, and search documents using the Document AI Warehouse user interface.

Document AI Warehouse

Training

Training and tutorials

Automating income taxes with Document AI

For the United States, Tax Day is upon us. Luckily, Lending Document AI can intelligently classify and parse many common documents used for tax preparation. Learn how to build a tax processing pipeline using Document AI.

Document AI Lending

Training

Training and tutorials

Smarter applications with Document AI, Workflows and Cloud Functions

With compute solutions on Google Cloud and Document AI, you can create seamless integrations and easy to use applications for your users. Document AI is a platform and a family of solutions that help businesses to transform documents into structured data backed by machine learning. In this blog post we'll walk you through how to use Serverless technology to process documents with Cloud Functions, and with workflows of business processes orchestrating microservices, API calls, and functions, thanks to Workflows.

Document AI Workflows

Training

Training and tutorials

Diving into your documents with Document AI

We recently announced the GA of the Document AI Platform, Google's solution for automating and validating documents to streamline document workflows. Important business data is not always readily available in computer-readable formats. This is what we consider dark formats such as pdfs, handwritten forms and images.

Document AI

Training

Training and tutorials

Using Document AI to automate procurement workflows

We recently announced the GA of the Document AI Platform, Google's solution for automating and validating documents to streamline document workflows. Important business data is not always readily available in computer-readable formats. This is what we consider dark formats such as pdfs, handwritten forms and images.

Document AI

Training

Training and tutorials

Building a document understanding pipeline with Google Cloud

Document understanding is the practice of using AI and machine learning to extract data and insights from text and paper sources such as emails, PDFs, scanned documents, and more. In the past, capturing this unstructured or "dark data" has been an expensive, time-consuming, and error-prone process requiring manual data entry. Today, AI and machine learning have made great advances towards automating this process, enabling businesses to derive insights from and take advantage of this data that had been previously untapped.

Document AI AutoML Vision AutoML Natural Language

Training

Training and tutorials

Automate Data Capture at Scale with Document AI

Earn a skill badge by completing the Automate Data Capture at Scale with Document AI quest, where you learn how to create a document processing pipeline that will automatically process documents. You will learn how to use the Document AI form processor to extract data from the documents and save the data.

Document AI Procurement BigQuery Google Maps API

Use case

Use cases

Introducing Document AI platform, a unified console for document processing

We recently announced the GA of the Document AI Platform, Google's solution for automating and validating documents to streamline document workflows. Important business data is not always readily available in computer-readable formats. This is what we consider dark formats such as pdfs, handwritten forms and images.

Document AI

Use case

Use cases

Add intelligence to your document processing with Google's Enterprise Knowledge Graph

With Document AI, we are bringing the power of Google search to help customers understand their documents. This means that the same Google knowledge graph technology that helps you find the name, address or phone number of your favorite restaurant can now enrich your document extraction with the right name, fully qualified address, and updated phone number.

Document AI Enterprise Knowledge Graph

Use case

Use cases

Templatic documents, such as receipts, bills, insurance quotes, and others, are extremely common and critical in a diverse range of business workflows. Currently, processing these documents is largely a manual effort, and automated systems that do exist are based on brittle and error-prone heuristics. A system that can automatically extract all this data has the potential to dramatically improve the efficiency of many business workflows by avoiding error-prone, manual work.

Document AI

Use case

Use cases

Going global: Workday uses Google Cloud AI to accelerate document processing

Scaling a business that sorts through millions of documents daily, across a global operation, is a tall order. Workday, with more than 3,400 core Workday Financial Management and Workday HCM customers, offers the Workday Expenses solution to provide a frictionless expense reporting experience for their customers. Here's how they did it using Google Cloud's Document AI for Procurement.

Document AI Procurement

Use case

Use cases

How Mr. Cooper is using AI to increase speed and accuracy for mortgage processing

Mr. Cooper Group is an industry-leading mortgage services provider serving customers through servicing, originations, and digital real estate solutions. Using Google Cloud AI and ML solutions, they created a highly reliable, cloud native document analysis and processing platform to process lending documents and unlocked new levels of accuracy and operational efficiency that help them to scale and control the cost at the same time. Read on to hear how they did it.

Document AI Lending

Code sample

Code Samples

Document AI Samples Repository

The repository contains Google-created samples and Community samples that demonstrate how to analyze, classify and search documents using Document AI.

Document AI

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Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2026-02-19 UTC.