Curate the right dataset for top-performing models
Find relevant data easily and curate healthy datasets for your models.
Task automation
Create processes that automatically tune into events in your projects, such as status updates, without any additional prompt from you. This reduces the time it’ll take for members to carry out these tasks manually, increasing efficiency.
Visualization
By being able to visualize the pipeline links, you can get a clear representation of the entire ML pipeline, helping you understand the flow of the automations.
Custom actions
Creating custom actions gives you the flexibility to create specific actions for your unique use cases and use them in your pipelines.
Python SDK
Empower your workflow with SuperAnnotate’s Python SDK, which offers seamless access to all UI functionalities at scale. Create projects, set up integrations, upload annotations, run predictions, filter and download datasets, and more.
Model training and auto inference
Automate the annotation process by creating models using your annotated data. You can later fine-tune the model based on your dataset and class structure.
Model versioning and comparison
Create models that meet your use case and track their accuracy parameters. Version each model, track their performance metrics, and compare different versions to gain valuable insights on model improvement.
Explore more features
Annotation services
Access a global marketplace of 400+ vetted, specialized, and professionally managed annotation teams.
Project and quality management
Manage the performance of projects, annotators, and annotation QAs.
AI data management and curation
Manage, version, and debug your data and create more accurate datasets faster.