Often, quality labeled data will be the blocker in experimenting with different model setups. Slow iteration speed with labeling can significantly slow down AI development.
Set up projects in minutes using Rapid’s suite of tools. Rapid also allows you to specify layers of review or consensus.
Write prescriptive labeling questions for taskers (single-select and multi-select) with real-time UI visualizations.
Pay per label, not hourly spend, with no committed spend. Create an account to access the pricing calculator.
Receive quality labels in a matter of hours from Scale’s Taskers spread out over multiple time zones.
Analyze tasker quality by using a golden set of ground truth results and gain granular insights on throughput metrics.
Rapid identifies and flags hard-to-label assets that might reveal ambiguities or edge cases in labeling instruction.
Use Nucleus to evaluate labels and model quality and curate new data for labeling. Then send to Rapid with a single click.
Leverage Scale’s trusted and trained labelers or simply use the labeling tools and bring your own annotators.
Achieve high-quality even on subjective tasks. Rapid's Spotter Pipeline objectifies performance for higher quality.
Scale 3D Sensor Fusion
We are pleased to offer reduced rates for students and researchers through our University Research Program.
“Scale Rapid has made it easier for us to gather annotations at a good price point. The UI is simple to navigate, and the built in worker evaluation pipeline and batch options saves us time and helps enforce best practices so that we can get high-quality training data.”
Software Engineer, Square
“Scale was able to adapt to admittedly challenging technical specification documents, some containing over 100 annotations for a single document. Scale Rapid helped us quickly adjust our project settings to present even clearer task instructions to labelers. The team at Scale was quick to adopt recommendations into their platform based on our feedback, often within the same day.”
Data Engineer, Uncountable
“Compared with other document annotation platforms we've tested, Scale provided not only a completely polished and well-performing annotation tool, but also offered a complete turnkey solution which included sourcing and managing the annotation workforce, with the results easily accessible via an API. Working with Scale over the past few months has saved us a lot of hassle and substantially accelerated our startup's progress, providing us with invaluable annotated data. Tony/Scale's customer service has assisted us with our rapid iteration so that we could perfect the annotation process, and they have quickly incorporated some of our suggestions to improve their API and platform even further”
“Properly labeling and counting timber isn't the most common deep learning use case, so we turned to Scale Rapid for our somewhat unique image data labeling needs. Scale's team was able to adapt to our requirements and deliver high-quality labeled data on schedule. Scale Rapid removes the pain and time burden of manually labeling data on a tight timeframe!”
CEO and Founder, TimberEye
“At X2, it became clear that our test users ask a very wide range of questions. We needed to classify this wide array of questions, and check for the performance of our model in answering them. We turned to Scale Rapid for quick turnaround time and robust results thanks to their helpful user interface and quick adjustments to our labeling instructions to handle edge cases specific to our users’ needs.”
Engineering Lead, X2.ai
“Scale Rapid truly stands out from other data labelling solutions in the market. We used it for text categorization and were impressed by the turnaround time and thoughtful design of the workflow for taxonomy creation, quality lab and built-in metrics for auditing along with the other features such as API access, price estimator, etc. which together make it a great self-serve solution.”
Senior ML Engineer, Grata