A document schema defines the structure for a document type (for example,
Invoice or Pay Stub) in Document AI Warehouse, where admins can specify properties
of different data types (Text | Numeric | Date | Enumeration).
Provides operations to create, fetch, update, and delete documents.
Document AI Warehouse uses documents as a data model to organize real world documents,
for example, PDF or .txt and their associated properties.
A folder serves as a container to group and label documents. Users can attach
a document to multiple folders and a folder can contain multiple documents.
It provides the capability to identify natural-language documents that satisfy
a query and optionally to sort them by relevance to the query. Using Document AI Warehouse,
customers can specify their query in string format in the search request.
Property filtering (Customer metadata filtering)
Mark a property filterable if you want to use that property to include or exclude
a portion of documents for a search. For example, you might make a property that represents a
"Vendor" filterable because your users want to search for invoices from a specific vendor.
Client libraries for Document AI Warehouse help support writing custom code that integrates with Google Cloud.
All services are accessible through the client libraries.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-25 UTC."],[[["\u003cp\u003eDocument AI Warehouse will be discontinued on January 16, 2025, requiring users to migrate their data to an alternative like Cloud Storage before that date to avoid data loss.\u003c/p\u003e\n"],["\u003cp\u003eDocument AI Warehouse provides features to manage access control, document schemas, individual documents, and to organize documents into folders.\u003c/p\u003e\n"],["\u003cp\u003eThe service supports both full-text search and property filtering to locate specific documents, as well as a custom synonyms feature for advanced search.\u003c/p\u003e\n"],["\u003cp\u003eA wide variety of file formats are supported, including common types such as PDF, JPEG, DOCX, TXT, and more, categorized by their MIME type and how they are supported.\u003c/p\u003e\n"],["\u003cp\u003eClient libraries for Java and Python are available to help with custom development for Document AI Warehouse.\u003c/p\u003e\n"]]],[],null,["# Supported features\n\n| **Caution** : Document AI Warehouse is deprecated and will no longer be available on Google Cloud after January 16, 2025. To safeguard your data, migrate any documents currently saved in Document AI Warehouse to an alternative like Cloud Storage. Verify that your data migration is completed before the discontinuation date to prevent any data loss. See [Deprecations](/document-warehouse/docs/deprecations) for details.\n\n\u003cbr /\u003e\n\nThis page describes the supported features and limitations for Document AI Warehouse.\n\nKey features\n------------\n\nFiles supported\n---------------\n\nFull details for [formats supported](/document-ai/docs/enterprise-document-ocr#supported_file_formats) and [MIME types](https://developer.mozilla.org/en-US/docs/Web/HTTP/Basics_of_HTTP/MIME_types/Common_types).\n\nProvisioning\n------------\n\nWorking with documents\n----------------------\n\nAPI client libraries\n--------------------\n\nClient libraries for Document AI Warehouse help support writing custom code that integrates with Google Cloud.\nAll services are accessible through the client libraries.\n| **Note:** These libraries are not required, but they can be used instead of the APIs discussed in the current documentation to make custom development easier."]]
