Automotive Data Engine

Unlocking Autonomy with best-in-class data.

The Automotive Data Engine

Scale’s Automotive Data Engine has everything you need to drive model improvements with data.

Data Labeling

Industry-leading annotation of 2D and 3D data sourced from multiple sensors. Achieve high quality data at low cost from ML-assisted labeling workflows, best in class operations, and advanced labeling interfaces.

Data Curation

Explore both labeled and unlabelled data. Understand dataset distribution, curate data matching target scenarios and send data for annotation.

Model Evaluation

Analyze the performance of your machine learning models. Explore model metrics, identify model weaknesses and evaluate your model on scenario tests.

Autonomy tech stack

How to Build Autonomy

Supported Data

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.

Label My Data→

Phases of Model Development

Scale partners with you at every stage of developing your model within the Data Engine.

1Base Phase

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.

2Improvement Phase

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.

3Target Phase

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.

Why Scale

Trusted by Leading Automotive Companies

Automotive leaders work with Scale for building autonomy for the following reasons:

Sure-Fire Improvements

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.

Maximum Performance

All the components of the Scale Data Engine maximize the value of each annotated label to improve model performance.

Faster Development

Scale accelerates the data engine loop - improving labeling speed, curating optimal datasets, and scaling up the workforce to drive faster development of AI applications.

RESOURCES