Document AI

Learn the required setup steps to start using Document AI.

Create a form parser and process a form PDF document using the Cloud Console.

Create and deploy a simple Document OCR processor in Java, Node.js, or Python.

In this codelab, you will perform Optical Character Recognition (OCR) of PDF documents using Document AI and Python.
You will explore how to make both Online (Synchronous) and Batch (Asynchronous) requests.

In this codelab, you will learn how to use the Document AI Form Parser to parse a handwritten form with Python.

Learn how to use Document AI Specialized Processors to classify and parse specialized documents with Python.

In this lab, you will focus on managing Document AI processors programmatically with the Python client library.

By using uptraining through Document AI Workbench, you can achieve higher document processing accuracy by providing additional labeled examples for Specialized Document Types and creating a new model version.

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

Learn how to configure and test an expense processor using human review to validate the results from the processor using the human-in-the-loop configuration and management tools.

In this codelab, you will learn how to ingest, process, and search documents using the Document AI Warehouse user interface. Sample PDF documents are provided for this codelab, including a license agreement, loan form, and order invoice.

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.