Create, use, and manage a custom document classifier

Use custom classifier to classify documents. Build it from the ground up with your own documents and custom classes. Its generative AI aspect allows few-shot learning and fine-tuning. These improve accuracy with fewer samples and corrections with iterative auto-labeling.

Custom classifier covers these three general use cases.

  • Pretrained model: Use the pretrained generative AI foundation model to quickly classify documents with your supplied labels.
  • Fine-tuning: Improve accuracy by training the generative AI foundation model on your own data and labels.
  • Train a custom model: Train a non-generative AI custom extractor using your own data and labels.

Custom classifier model versions

Confidence scores are supported for custom classifier models in Preview. For best performance, use them with fine-tuned models.

Model version Description Release channel ML processing in US/EU Fine-tuning in US/EU Release date
pretrained-classifier-v1.5-2025-08-05 Production-ready model powered by the Gemini 2.5 Flash LLM. Also includes advanced OCR features. This pre-trained model can be used without prior training. It supports zero-shot classification and provides better support for the catch-all class. Stable Yes US, EU (Preview) August 5, 2025
pretrained-classifier-v1.6-2026-03-09 Release candidate powered by the Gemini 3.1 Flash LLM. Release Candidate Yes No March 9, 2026
pretrained-classifier-v1.6-pro-2026-03-09 Release candidate powered by the Gemini 3.1 Pro LLM. Release Candidate Yes No March 9, 2026

Create a custom classifier in the Google Cloud console

You can create custom classifiers that are specifically suited to your documents and trained and evaluated with your data. This processor identifies classes of documents from a user-defined set of classes. You can then use this trained processor on additional documents. You typically would use a custom classifier on documents that are different types, then use the identification to pass the documents to an extraction processor to extract the entities.

For the general process to create and use a processor, see the How to section.

You can make your own configuration choices that suit your workflow.

To follow step-by-step guidance for this task directly in the Google Cloud console, click Guide me:

Guide me

Before you begin

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Roles required to select or create a project

    • Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
    • Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

    Go to project selector

  3. If you're using an existing project for this guide, verify that you have the permissions required to complete this guide. If you created a new project, then you already have the required permissions.

  4. Verify that billing is enabled for your Google Cloud project.

  5. Enable the Document AI, Cloud Storage APIs.

    Roles required to enable APIs