Noisy labels make noisy AI. Get a complete solution for improving your models and data with Labelbox.
Why choose Labelbox over Snorkel AI?
Everything in one place
In addition to labeling tools, Labelbox offers data curation, AI-assisted labeling, model training and diagnostics, along with labeling services, all in one platform.
Easy setup, intuitive UI
Labelbox's intuitive interface is easy for any team to use, with self-serve onboarding and guided implementation across the platform to help you get set up quickly.
Advanced configurability and flexibility
Create customizable QA and review workflows, flexible ontology setups, and unique task structures to meet your project-specific 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.
Miao Zhang, AI Scientist
I already use Snorkel as a platform but I’m looking for a labeling service
Labelbox offers the best of both worlds—a world-class all-in-one platform, and a team of specialized experts to help you label data faster. Our approach makes it easy to centralize and manage your entire labeling data pipeline.
The Labelbox platform is built to be scalable, customizable, and allow for traceability to manage complex workflows, while Labelbox Boost offers on-demand labeling services and AI expertise. Our machine learning teams are experienced in many AI use cases and give you the resources you need to iterate better and improve model performance.
I just want a cost-effective solution….
While Snorkel’s weak supervision approach is more cost-effective for programmatically labeling massive amounts of data, it may cost you more in the long run to organize, QA, and actually use that data for model training.
In cases where labeling is incorrect, your team would need to invest extra time to fix it which would cause delays in your labeling project. In addition, you'd then have multiple models to improve and correct - the model being built for production AI and the model that is supposed to help your labeling process.
Labelbox offers a more straightforward process that doesn't require you to juggle models. Our approach is designed to cut labeling costs by up to 70% and improve labeling efficiency by giving you insight into model predictions and labeled and unlabeled data.
But Snorkel claims to have strong use cases
Snorkel may work for some use cases, but programmatic labeling doesn’t actually work across all data modalities. Using heuristics for image and video projects becomes much harder than hand labeling and using ground truth. If you want the flexibility to expand to either of these data types in the future, you might want to reconsider using Snorkel AI as your labeling platform.
Labelbox offers labeling for a wide range of use cases, including Image, Audio, Video, 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.
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%.
Snorkel AI works for me now, why should I switch?
While a weak supervision tool like Snorkel may be useful for pre-processing a large amount of data, this approach isn't the best option for teams looking to scale their AI projects in the long run. After pre-processing, machine learning teams still need a way to browse, curate, and QA their data.
As an alternative, Labelbox is a platform designed to grow with you. Our software infrastructure provides a place to feed and pre-process, browse & QA, and manage all of your data in one single platform.
But Snorkel AI meets my security and compliance needs
Snorkel AI’s security processes are opaque and not readily available. It’s unclear how their platform is designed to ensure your data is protected or what security measures they invest in to make sure your data stays your data.
As an alternative, Labelbox operates on a security-by-design principle, 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.
I don't want a Snorkel AI alternative, I'm looking to improve model performance with a better solution
Labelbox isn't just an alternative to Snorkel’s labeling tool, our all-in-one platform allows you to connect and manage data like never before.
Our approach enables AI teams to use 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.