doccano

At a glance

• Editor score
  7.1 / 10
• Pricing
  Open source
• Best for
  Open-source text annotation projects
• Paid from
  Free
• Supported modalities
  text, image, audio
• Facts checked
  22 Sep 2026

• Where it wins

  • Supports classification, sequence labeling, and sequence-to-sequence annotation
  • Includes collaboration, custom labels, and annotation guidelines
  • Offers dataset import/export, REST APIs, and CLI-based pre-annotation

• Where it doesn't

  • Self-hosted deployment requires teams to manage the installation environment
  • Its verified integrations are narrower than general-purpose labeling tools
  • Its strongest documented workflows center on text annotation

Our verdict on doccano

doccano is an open-source data-labeling and annotation tool for machine learning practitioners. It is designed for teams working on text classification, sequence labeling, named-entity annotation, and sequence-to-sequence projects. Teams can create projects, define custom labels and annotation guidelines, import datasets, collaborate with project members, annotate examples, and export labeled data. The product also supports image and speech project types through its client API, with web, self-hosted, Android, and iOS platforms listed.

The main strength is its focused annotation workflow. Project members can work together on labeling tasks while using shared guidelines and custom ontologies. Human review is supported, and model-assisted pre-annotation is available through the client CLI. This makes doccano a fit for teams that want a labeling interface connected to scripts or machine learning models without moving away from an open-source deployment model. REST API access adds another path for integrating projects with surrounding data and model workflows.

Its scope is more focused than that of broader general-purpose labeling tools. Text workflows are the clearest fit, while image and audio support is exposed through additional project types in the client API rather than presented as the central product focus. Deployment is self-hosted, and installation can be handled with pip or Docker and Docker Compose. Choose doccano when open-source ownership, collaborative text annotation, custom labeling schemes, and API access are priorities. Teams seeking a wider verified integration ecosystem or a hosted paid-tier model should consider an alternative with those capabilities.

Your product? Our editors can test doccano in depth and publish a review, labelled as paid · from $149/mo →

doccano pricing

doccano fact sheet

Alternatives to doccano

• Label StudioA flexible open-source labeling platform with broad annotation, export, and deployment options.9.3
• CVATA broad annotation toolkit with free access, AI assistance, collaboration, and self-hosting.9.2
• ArgillaA free, open-source labeling workspace with strong text and image support.9.0

See all doccano alternatives →

Featured on iTechGuides

doccano is listed in our AI Data Labeling Tools directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 7 Oct 2026 · How we research and update