AI teams choose Labelbox over Snorkel to generate the highest quality data
Why choose Labelbox over Snorkel AI?
High-quality data
Generate powerful human data to differentiate your generative AI solutions, whether building frontier models or performing post-training and RLHF.
Rapid delivery with global workforce
Deliver data on-demand by accessing Labelbox’s network of highly-skilled experts and reach the scale you need to accelerate your AI project timelines.
End-to-end platform with built-in control and customization
Easily create custom workflows and engage in real-time communication with external labelers to align on outputs through an open, transparent platform.
Labelbox has enabled us to dramatically improve our model performance for our most critical AI initiatives by tapping into their network of expert labelers and platform for human evaluation. In the past two months, our document intelligence teams are seeing a 2X increase in data quality compared to other vendors. We continue to work with Labelbox to further enhance our genAI capabilities and to hit our development timelines.
Generate guaranteed high-quality data with an expert labeling workforce
Snorkel does not offer SMEs or on-demand labeling services that are often necessary for AI alignment in more complex generative AI or LLM tasks. The inability to combine a human-in-the-loop approach with an annotation platform can cause fragmented labeling strategies for teams, as well as decrease overall data quality.
In order to provide the highest quality data, Labelbox operates the Alignerr community, a network of 10,000+ highly educated experts that span numerous languages and subjects–with the ability to rapidly attract new talent in areas needed. We stand behind the quality of our labeling services, so if a labeled dataset does not meet a customer’s quality standards, we will happily do it again for free.
Increase throughput with best-in-class software
Although Snorkel believes their programmatic labeling approach is crucial to increasing throughput, this is only efficient for initial labels which can often be lower quality than human generated labels. Their technical platform which requires additional expertise for usage, coupled with rule-based conditions that change over time, leads to high maintenance and upkeep. A programmatic approach can also cause limitations around labeling across all data modalities.
Software is an essential part of the Labelbox DNA. The unified platform delivers powerful labeling tools and AI-assisted automation to facilitate the rapid generation of high-quality data. Load, curate, label, and evaluate data from over 25+ different data sources in a unified, transparent, and intuitive platform. Built-in editors are available for a wide range of data types that include multimodal chat, LLM prompt/response, video, image, audio, PDF, geospatial, and more to support a wide range of tasks with a simple click.
Simplify management with transparency and flexibility
Snorkel is a technical platform that requires users to have coding expertise to create very basic label functions, which can cause customizing project workflows to be challenging and time consuming. While Snorkel does provide some insight to labeling accuracy, there is a lack of granular, actionable metrics on performance analytics and only basic chat features for communication.
We understand that every AI project looks a little different. For teams that just need data quickly, the labeling service powered by Alignerrs provides a hands-free process backed by software, expert labelers, and proven processes. Teams that want more control can use the Lablebox platform to create custom multi-step workflows, monitor key metrics to measure granular performance per individual labeler, and utilize real-time collaboration tools to track every stage of the labeling process - all with no additional coding required.
Accelerate AI alignment for critical tasks
Snorkel does not offer any additional built-in tooling around AI-assistance, model-assisted labeling, or the ability to visually curate and search through data.
Automation with AI-alignment is a key priority to fulfilling Labelbox’s goal of having customers label less data, more quickly. With model-assisted labeling, auto-labeling, visual data curation, and the ability to automatically create custom workflows to streamline human-in-the-loop review, customers are able to rapidly scale up their data generation initiatives while simultaneously saving time and cost.
Our labeling strategy was very disjointed before Labelbox. We were missing a scalable solution to label data, source labelers, and apply automation techniques. Out of the vendors we evaluated, Labelbox was the clear winner. In our POV, Labelbox sped up our end-to-end project deployment by 85% and increased our label accuracy by 5-10%.