The Automotive Data Engine
Scale’s Automotive Data Engine has everything you need to drive model improvements with data.
How to Build Autonomy
Best-in-class data to fuel autonomy
Scale has pioneered in the data labeling industry by combining AI-based techniques with human-in-the-loop, delivering labeled data at unprecedented quality, scalability, and efficiency.
Phases of Model Development
Scale partners with you at every stage of developing your model within the Data Engine
Scale’s Data Engine helps you collect and label a base dataset to unlock initial model performance. Our platform lets you randomly sample data or add constraints (ex. Time of day = night) matching your intended distribution.
In this phase, the Data Engine ensures new datapoints continually challenge your model and maximally improve performance. To achieve this, Scale offers both automated (ML-based) and manual curation methods.
Scale helps you collect and curate data targeted to specific scenarios with Natural Language Search and Autotag, we then label that data and improve your model performance on those specific scenarios. Scale helps you close the loop by evaluating your model on scenarios tests.
Trusted by Leading Automotive Companies
Automotive leaders work with Scale for building autonomy for the following reasons:
Data is the sure-fire way to improve your models. With every larger/higher quality/more diverse dataset, Scale helps your machine learning models improve.
All the components of the Scale Data Engine maximize the value of each annotated label to improve model performance.
Scale accelerates the data engine loop - improving labeling speed, curating optimal datasets, and scaling up the workforce to drive faster development of AI applications.