Don’t create labels with Scale AI. Create breakthroughs with Labelbox.
Compare Labelbox versus Scale AI
Software-first approach
Labelbox is built with 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
Labelbox unites data labeling software and services, data curation, model testing and evaluation into a single enterprise ready platform. This integrated approach enables ML teams to build AI applications, remarkably fast.
Configurable and flexible
We understand that every ML project might look a little different. Create custom workflows for QA sequences, labeling and anything else you need to ensure higher quality data in less time with Labelbox.
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%.
Noe Barrell, ML Engineer
I heard Scale AI is building software to manage data and evaluate models...
Scale AI offers features across Nucleus, Rapid, and Studio that can be used to address different parts of the AI lifecycle, but each product is its own separate entity with different pricing and workflows.
This unbundled approach means that you’ll wind up spending even more money on products that don’t have an integrated workflow across data curation, labeling, and model evaluation, which means 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.
I don’t want to spend more time overseeing my labeling process….
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 and visibility needed for your team to maximize efficiency and gains in model production.
The lack of quality dashboards, individual labeler insight, and customizable review queues leads to difficulty in scaling your labeling processes. Labelbox gives you visibility and quality with actionable metrics that drive efficiency. Plus, we’ll work with you to find the most efficient workflows and drive down labeling costs.
But I don't have a dedicated labeling team in-house
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.
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.
But I heard Scale AI labels large volumes of data quickly for a low cost…..
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 when thinking about your long-term AI roadmap. Coupled with poor labeling quality and the lack of actionable metrics to drive efficiency, you’ll find that labeling spend with Scale quickly grows proportionally to the volume of data labeled. In short? Inefficient data workflows = more money spent.
With Labelbox, we encourage active learningworkflows 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.
I’m concerned about security and privacy, I don’t want others using my data…
Labeling service providers like Scale 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 create pre-labels. However, all efficiency gains stay with Scale AI and your data is used to improve their business.
At Labelbox, In addition to being SOC2 Type II certified as well as GDPR and HIPAA compliant, 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%.
I don’t just want to get data labeled, I'm looking for a better solution that will improve model performance
Labelbox goes beyond data labeling. Our all-in-one platform allows you to connect, and manage data like never before.
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.
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.