Scope
Define the labeling task
Choose representative sensor data, a label taxonomy, and quality checks for your pilot.
Agentic Labeling
Auto-label with AI. Review with context.
Connect model-assisted labeling, human review, and curated training data in one Physical AI workflow.
Scope
Define the labeling task
Assist
Generate and review pre-labels
Refine
Turn corrections into training data
Agentic Labeling
Build automation around your data.
Validate a useful workflow before scaling it. Model choice, review effort, and deployment depend on the task.
Assist
Generate and review pre-labels
Use a supported model to generate pre-labels. Review results against your project’s labeling instructions.
Refine
Turn corrections into training data
Correct failures, curate reviewed data, and evaluate the next model version before expanding coverage.
Explore Models
Find a starting model.
Explore capabilities and integration details in the catalog. Availability and deployment options vary by model.
Agentic Labeling
Start with a representative pilot.
Bring your sensor data, labeling requirements, and review criteria. Together, we can scope a workflow for your task.