AI teams choose Labelbox over Scale AI to generate the highest quality data
Why AI leaders choose Labelbox over Scale AI
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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
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.
Essential control
Create custom workflows and engage in real-time communication with external labelers to align on outputs through an open, transparent platform.
How are Labelbox and Scale different?
Labelbox and Scale both provide labeling services; however, only Labelbox delivers the three essential parts to a modern AI data factory: a transparent labeling platform, expert labeling services, and proven expertise and processes to ensure the highest quality data.
Scale | Labelbox | |
User-facing platform | Primarily functions as a tech-enabled BPO with black box software not readily accessible to customers. | Fully-managed service with a transparent software platform that includes advanced tooling and an intuitive interface. |
Product portfolio | Multiple, siloed products. Limited integration between data curation, workforce management, annotation, and evaluation products. | Single, unified platform with data curation, labeling, AI-assisted alignment, workforce management, QA, and model evaluation. |
Data types supported | Supports text, image, video, audio, and 3D data. | Supports multimodal chat, conversational text, image, video, audio, geospatial, tiled, document, and HTML data. Limited support for 3D. Learn more. |
Expert labeling services | Scale operates Outlier, which offers data labeling services in over 80 languages with expertise in coding, finance, STEM, and more. | Labelbox operates Alignerr, a global workforce of SMEs specializing in diverse languages with expertise in coding, finance, STEM, writing, and more. |
Data curation | Scale’s Nucleus allows for data curation and visualization. No support for text or audio data. Limited similarity search with a maximum of 12 images. | Labelbox Catalog is used to curate, visualize, and do AI-assisted search of most data modalities—images, video, text, geospatial, audio, & docs. |
Multimodal annotations | No. Lacks built-in features to support multimodal annotations. | Yes. Multimodal chat feature allows users to evaluate models with text data alongside image, video, audio, and document (pdf) files. |
Automation & model-assisted labeling | Scale’s GenAI platform can fine-tune and deploy foundation models. Offers AI-assistance with semantic segmentation and active learning. | Labelbox's Foundry leverages numerous foundation models to generate pre-labels and automate workflows. AI-assistance is integrated throughout. |
Quality assurance | No insights on labeling time spent by human annotators, individual labeler performance, or the average quality of a labeled asset. | Dashboards report granular labeling metrics of individual labelers and provide custom review workflows and SLA monitoring. Detailed QA metrics available. |
Quality guarantee | No | Yes. Labelbox’s Labeling Service quality guarantee ensures the labels will meet customer’s quality standards or they will be re-done for free. |
Real-time collaboration | Limited. Only offers a comment feature for computer vision (image/video) and document tasks. | Yes. Real-time collaboration with both internal and external teams through built-in features like issue reporting and project-level comments. |
Deployment models | As a service (cloud agnostic) and on-premise. | As a service (cloud agnostic) with advanced cloud storage integrations to simplify connecting to existing data stores. |
"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 previous vendors. We continue to work with Labelbox to further enhance our genAI capabilities and to hit our development timelines."
Human data lead
Generate high-quality data, guaranteed
Scale AI’s dashboard provides an overview of different tasks and labeling quality but lacks granular insights. Human data labelers from Scale’s workforce, Outlier, have expressed issues around the disorganization and unreliability of their tasks. Together, these issues can impact the efficiency and accuracy of the new data.
Labelbox operates the Alignerr community, a network of 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. We focus on transparency with both our customers and Alignerrs.
Labelbox also has built-in quality control mechanisms throughout the platform. Performance metrics are available at the workspace, project, and individual labeler level, providing actionable insights to continually improve data quality.
![Increase throughput with best-in-class softawre](/_next/image/?url=http%3A%2F%2Fimages.ctfassets.net%2Fj20krz61k3rk%2F7jM4Lmz78zwpO0UNtKmhnX%2F3e39f6cd27ef326017c15d1a35c71ab8%2F_discover_labelbox.png&w=3840&q=70)
Increase throughput with best-in-class softawre
Scale AI takes a traditional approach to outsourced labeling and resembles a black box. Primarily functioning as a labeling service, they lack the control and visibility needed for your team to maximize efficiency and gains in model production.
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, with either a hands-off approach or total control of the end-to-end workflow. Granular performance metrics are available so you can monitor (and adjust as needed) all areas of the data labeling process.
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Create transparent, customizable and unified projects
Scale AI offers features across Nucleus, Rapid, and Studio that address various parts of the AI lifecycle. Each product is its own separate entity with individual pricing and workflows. This lack of a unified workflow can hinder collaboration among internal and external teams, leading to silos and reduced visibility across different product lines.
We understand that every ML project might look a little different. For teams that just need data quickly, the Labelbox Labeling Services provides a fully-managed process backed by software, expert labelers, and proven processes. For others, they can lean into the platform to create custom multi-step workflows, track key metrics, and collaborate in real-time with internal and external teams.
![Increase efficiency with automation and AI-assistance](/_next/image/?url=http%3A%2F%2Fimages.ctfassets.net%2Fj20krz61k3rk%2F9Lr8vU37vPZqQ66dobqm8%2Fb504452cd87bfe404d72271e5988b31e%2FAutoQA__1_.png&w=3840&q=70)
Increase efficiency with automation and AI-assistance
While Scale AI offers foundation models for fine-tuning LLMs and some AI-assistance tools, decreasing labeling time and costs through automation is not their primary focus. Customers share that their labeling spend with Scale quickly grows proportionally to the volume of data labeled. In short? Lack of automation built throughout the platform means more money and time spent on datasets.
Automation is a key priority to fulfilling Labelbox’s goal of having Alignerrs and customers label less data, more quickly. With model-assisted labeling, auto-labeling, and the ability to automatically customize 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.
"Labelbox’s combination of an end-to-end platform solution with feature rich tooling and a vast range of expert labeling services was key to us choosing them as our labeling partner. With Labelbox, our team can quickly iterate and create high quality datasets for our gen AI initiatives."