Open source tools like CVAT only get you so far. Choose Labelbox for a complete solution that grows with you.
Compare Labelbox versus CVAT
Build better AI, faster
Labelbox goes beyond data annotation. Our three core products: Catalog, Annotate, & Model work in tandem to help AI teams centralize the maintenance and creation of high-quality training data needed to accelerate model production.
Secure and scalable
Labelbox is designed with security in mind, with features that give you full control over your data. In addition to offering hybrid cloud integration, Labelbox is SOC2 Type II certified, and GDPR and HIPAA compliant with annual external audits
Enterprise-grade features
Labelbox offers rich analytics, advanced workflows, and more data modalities to cater to all of your unique AI projects. Easily connect to tools you already use, like Databricks, GCP and Azure, through our extensive partner network.
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’m looking for a solution that offers annotation software and labeling services….
While open source tools like CVAT are good for testing proofs of concept with limited datasets, they aren’t efficient in helping you reach production AI. There’s no option to integrate an external labeling team for your project needs that can help with scaling your efforts.
In comparison, Labelbox offers the best of both worlds. You can choose to label your own data through either an internal team or BPO, or use Labelbox Boost’s on-demand labeling services and AI expertise. Our specialized machine learning teams are experienced in many AI use cases and give you the resources you need to iterate better.
Isn’t CVAT more cost-effective as an open source tool?
A free solution doesn’t guarantee quality. When high-quality data is a differentiating factor for the most successful AI teams, you want to make sure you’re optimizing for quality over cost. When you optimize solely for cost, you often get what you pay for – which is why choosing a cheaper open-source solution like CVAT that doesn’t promote scalability is a significant risk.
Labelbox’s AI-first approach prioritizes obtaining high-quality training data. We’ve designed our platform and workflows to help you achieve quality with less spend. From model-assisted labeling to custom active learning workflows, investing in Labelbox ensures better lifetime value for your AI team. You don’t have to sacrifice cost vs quality – you get the best of both worlds with Labelbox.
Doesn’t CVAT have strong use cases for computer vision?
While CVAT does support workflows for computer vision tasks, teams are only limited to this data modality. CVAT does not offer data annotation for Text, Audio, Documents, or Geospatial (tiled imagery). If you plan to expand to any of these data types in the future, you might want to reconsider using CVAT as your labeling platform.
Labelbox offers data labeling for a wide range of use cases, including Image, Video, Audio, Text, Conversational Text, PDF / Documents, Geospatial (Tiled Imagery), and Medical Imagery (including whole-slide pathology scans). Choosing a vendor that supports a wide variety of data types gives you the flexibility to scale as your AI team and projects grow.
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.
What if I have questions or need support?
Open source tools like CVAT only offer community-based support through forums and asking other users. Teams that build in-house are also limited to their own engineering and data science resources with no access to subject matter or vetted labeling experts.
Labelbox's robust support team includes experts that specialize in machine learning, data annotation, and labeling operations. From troubleshooting issues to guiding AI teams through industry best practices, you get dedicated access to professionals that will help you scale.
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. Our approach enables AI teams to use custom workflows, model-assisted labeling, active learning, and advanced data selection methods to improve model performance while keeping data labeling costs to a minimum.
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.