Proven visibility & quality
We take a software-first approach to data labeling and automation. In-depth performance metrics are built throughout at the workspace, project, and individual labeler level to give your team visibility into quality every step of the way.
Everything in one place
Rather than having to rely on numerous applications, we offer three core products: Catalog, Annotate, & Model. They work in tandem to help AI teams dramatically centralize the creation and maintenance of high-quality training data needed to accelerate model production.
Configurable and flexible
We understand that every ML project might look a little different. Create custom workflows to fit your ML pipeline with UI features and APIs to easily curate, annotate, and evaluate model performance.
With Labelbox, we’re able to generate high-quality annotations by allowing our team of domain experts and labelers to collaborate more efficiently. The workflow we’ve built queues up all the work for our labelers to create image annotations, which are then sampled and reviewed by experts, and fed into ML models to make better AI diagnoses.
Miao Zhang, AI Scientist
While Scale AI has products across Nucleus, Rapid, Studio, and more, each product is its own separate entity with different pricing packages and workflows. This setup doesn’t encourage a flexible workflow across data curation, labeling, and model evaluation, and AI teams can find themselves working in silos.
Labelbox Catalog helps AI teams prioritize and select the most important data to reduce labeling spend and time to model development, while Annotate gives you full visibility and control, and lastly, Model helps track model performance and identify model errors to dramatically improve performance.
Scale AI takes a traditional approach to outsourced labeling and can often resemble a black box. Primarily functioning as a labeling service, they can lack the control & visibility needed for your team to maximize efficiency and gains in model production.
Labelbox is built to be a software-first company. From the start, we’ve been on a mission to provide leading AI teams with everything they need to build AI products faster than ever. We recognize that the hardest part about building quality models is obtaining high-quality training data. As such, we’ve built quality dashboards, at both the workspace and project level, for teams to consistently track labeling efficiency, throughput, and quality. Plus, we’ll work with you to find the most efficient workflows and drive down labeling costs.
We’ve got you covered with Labelbox Boost. Our on-demand labeling services and AI expertise gives you the resources you need to iterate better. Unlike Scale AI that charges per labeled object, Labelbox Boost bills per screen activity time so your costs stay the same even as projects scale.
Also, pay attention to the numerous reviews of Scale Rapid's workforce quality. As an alternative, our on-demand labeling services and AI expertise through Labelbox Boost is designed to take you from initiation to production-scale labeling in just a few days.
Reducing our data requirements is huge because we can get the same amount of improvement in our model’s performance in half the time and with half the effort. This was enabled through targeting the model’s weaknesses with Labelbox’s Model product and then being able to prioritize the right data through Catalog. By doing so, we’ve reduced our labeling spend and data needs by over 50%.
While Scale AI might seem like a plausible solution to getting data labeled quickly, it isn’t the most efficient use of cost and resources in the long run. Coupled with poor labeling quality and the lack of actionable metrics to drive efficiency, Scale AI isn’t the best option for teams who wish to scale their training data into production.
When you look at your long-term AI roadmap, you’ll find that labeling spend with Scale quickly grows proportionally to the volume of data labeled. In short? More data = more money spent. With Labelbox, we encourage active learning workflows across Catalog and Model to help you prioritize the most high-impact data for labeling. By doing so, you’re able to label in priority and customize your review workflow to decrease review time, labeling time, and cost.
It might seem like Scale meets all of your security needs, however, labeling service providers often use customers’ labeled training data to improve their own pre-labeling algorithms. Scale offers a Model Zoo with pre-trained models for teams to use to help create pre-labels. However, all efficiency gains stay with Scale AI and your data is used to improve their business.
At Labelbox, we believe that your data should stay your data. To create the most effective pre-labels, you should be using your own model or an off-the-shelf model of your choice. Rather than provide teams with a library of models, we’ve carefully designed features within Labelbox to empower teams to reduce human labeling through automation by 80%.
In addition to being SOC2 Type II certified as well as GDPR and HIPAA compliant, Labelbox gives you full control over your data. Easy export and deletion options mean you can use Labelbox as a secure, scalable, and enterprise-ready platform to house all your unstructured and structured data.
Labelbox isn't just a Scale AI replacement, our all-in-one platform allows you to search, visualize, and annotate your data like never before.
To further accelerate model production, we offer active learning workflows between Model and Catalog to help improve model performance. Our flexible API and webhooks projects give you full control so you can set up customized workflows based on your AI team's unique project needs.
AI has been crucial for us to accomplish our goals and we’re using Labelbox in many of our projects and processes. It allows us to standardize how we create and manage data all in a single location and using their automation features, we’ve seen a reduction in labeling times by 2x.