doccano
7.9#3 in ai data labeling toolsFree planFree planAndroidiOSWebAPI
Visitdoccano vs Prodigy
What both publish
| Fact | doccano | Prodigy |
|---|---|---|
| Installation | The official project documents installation with pip, Docker, and Docker Compose. | Licensed users install through pip using a private download index and license key, or install a downloaded wheel. |
| Licence | The software is distributed under the MIT licence, allowing use, modification, redistribution and commercial sale subject to licence notices. | Prodigy is proprietary commercial software; the licence is revocable, non-exclusive and non-transferable, with some bundled components potentially under open-source licences. |
| REST API | A RESTful API is provided for connecting scripts and machine-learning workflows. | The web application communicates through a REST API powered by FastAPI, with interactive documentation available at the local /docs endpoint. |
doccano plans
- doccano open-source self-hostedFree
- MIT-licensed softwareFree
Prodigy plans
- Personal$390, paid once
- Company$490, paid once
Pick doccano if…
doccano suits teams and practitioners who need to label datasets collaboratively, including for classification, entity recognition, or summarization. It also fits users who want self-hosting and API-based integration with scripts or models.
Pick Prodigy if…
Prodigy suits developers and machine-learning teams comfortable with Python and the command line. After setup, its annotation web app can also be used by annotators without programming experience.