BasicAI vs Doccano
BasicAI
basic.aiDoccano
doccano.github.ioSide by side
| Figure | BasicAI | Doccano |
|---|---|---|
| Price from | $550/mo | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Data Labeling Software | 8.0 (#11) | 8.8 (#2) |
| Deployment | BasicAI offers on-premise deployment options, with professional deployment and maintenance services and data kept within the customer’s systems. | The repository lists one-click deployment options for AWS and Heroku, and the guide supports installation locally or in the cloud. |
| Integrations | The platform page says users can import and export data from AWS, Google Drive, and Dropbox. | The auto-labeling guide demonstrates Amazon Comprehend Sentiment Analysis and allows users to configure a custom REST API. |
| Support | The company provides technical support and offers a dedicated support plan with its private-cloud deployment. | The project directs users to its FAQ and invites them to contact the author for help and feedback. |
Plans
In their own words
Doccano
Doccano is a free, open-source data-labeling tool for machine-learning practitioners. Its supported annotation tasks include text classification, sequence labeling, and sequence-to-sequence annotation, with uses such as sentiment analysis, named entity recognition, and text summarization. Users can set up projects, import datasets, add collaborators, annotate examples, and export labeled data. REST APIs let scripts connect to Doccano for model-assisted labeling, and multiple people can work collaboratively. Installation options include pip, Docker, Docker Compose, source, or cloud deployment. The installation guide lists Linux, Windows, and macOS machines running Python 3.8 or later. SQLite 3 is the default database; PostgreSQL configuration is described, and MySQL is mentioned as an option. Imported datasets can be stored using Amazon S3 or Google Cloud Storage. The project also lists mobile and multi-language support, emoji support, and a dark theme. Integration guidance demonstrates Amazon Comprehend Sentiment Analysis and custom REST APIs for auto-labeling. One upgrade caveat is important: the installation guide warns that an upgrade using SQLite 3 can cause database loss.