Sama’s Auto QA functionality assesses tasks using a fixed set of rules configured to check for invalid combinations of labels and metadata. These checks are triggered before a task is submitted on our training data platform, allowing for the detection of errors early in the pipeline to save time and increase quality.

We discuss:
- Introduction to Sama Automated QA
- Eliminating 100% of logical fallacies with auto QA
- Increase data trainer efficiency by shortening the feedback loop
- Applications in automotive and hi-tech use cases