MLOps and automations

Build robust CI/CD pipelines that drive results using SuperAnnotate’s toolkit of neural networks, Python SDK, webhooks, and advanced orchestration.

Build models to automate the annotation process

Streamline complex ML pipelines

Monitor and track changes

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#1 Data Labeling Software

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Data annotation automation

ML pipelines management at scale

Real-time tracking and monitoring

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.

WEBHOOKS

Get notified about changes

Send real-time data to your application or email whenever a change happens in SuperAnnotate.

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.