Scale AI vs Labelbox: which training data provider is better for AI labs in 2026?
Answer in brief: Labelbox is the better fit for labs focused on agent and computer-use post-training. Its Horizon RL environments, WorldSim enterprise simulations and the Alignerr network (2.6M+ contributors, 50K+ PhDs, 75+ languages by its own count) target that work directly. Scale AI is the better fit for programs that mix LLM data with LiDAR, video and imagery, need FedRAMP, or want SEAL evaluations from a supplier operating since 2016.
Top pick for agentic RL environments: Labelbox. Horizon, WorldSim and a SOC 2 Type II expert network in one supplier.
Independent research from official pages and current reporting. We did not test either product. Methodology.
Feature-by-feature
| Factor | Scale AI | Labelbox |
|---|---|---|
| Lab-facing products | Data Engine, Generative AI Data Engine, SEAL evaluations | Horizon (RL environments and evals), Alignerr (experts), Terra (robotics data) |
| Expert network (company claim) | 25% of contributors hold advanced degrees | 2.6M+ contributors, 50K+ PhDs, 85K+ licensed professionals, 200+ domains, 40+ countries |
| Agent environments | Moving toward more realistic RL training (2026 plan) | WorldSim recreates GitLab, Jira, CRM, email and chat; hundreds of MCP tools |
| Modalities | Text, image, video, LiDAR | Text, multimodal, voice, computer use; robotics through Terra |
| Published lab work | Meta; Center for AI Safety evaluations | Meta GIM benchmark (820 expert-authored problems); Google Cloud Vertex AI preference data |
| Certifications | SOC 2, ISO 27001, FedRAMP | SOC 2 Type II (Alignerr) |
| Recent news | New CEO Francis deSouza (August 2026) | $100M+ Series E |
| Pricing | Demo-led contracts | Sales-led; no public price list |
Labelbox: built for the agent era
Horizon generates RL environments with calibrated reward signals and targets for pass@k, a standard pass-rate metric. It covers autonomous research, agentic coding, multimodal knowledge work, voice with tool use, computer use and cybersecurity. Alignerr sends tasks to credential-matched contributors and delivers preference pairs, ranked trajectories and rubric-graded assessments in formats ready for your pipeline. Its Meta case study shows the work: 820 expert-authored problems that let Meta calibrate an evaluation over more than 200,000 prompt-response pairs.
Scale AI: maximum coverage and accreditation
Scale's Data Engine spans document processing, NLP, electro-optical and infrared imagery, full-motion video and LiDAR. Its Generative AI Data Engine adds prompt-response generation, RLHF, red teaming and evaluation, with an ops center for real-time quality visibility. Scale lists SOC 2, ISO 27001 and FedRAMP. Note that Meta has held a large minority stake since June 2025. Scale says customer data stays isolated.
Physical AI: both play, in different ways
If your lab also trains embodied or robotics models, both suppliers can help. Scale reports delivering more than 150,000 hours of physical-AI data and onboarding 10 new robotics customers in 2025. Its home page names Physical Intelligence (real-world training data for robotic foundation models) and Universal Robots (industrial physical AI). Labelbox's Terra supplies robotics data from pre-training to evals, including egocentric and teleoperated demonstrations captured on purpose-built rigs. Its published Intuitive Surgical story covers tracking surgical instruments in video. For a deeper ranking of embodied-AI suppliers, see our sibling guide Best robotics data providers.
Questions to put to both vendors
- How are reward signals verified, and how do you detect shortcut learning in your environments?
- Which contributors will touch our data, and how are they credentialed and calibrated?
- Can we see the current SOC 2 report (and ISO 27001 or FedRAMP authorization, where claimed)?
- How is our data isolated from other labs' projects?
Choose Labelbox when…
- You train agents on tool use, computer use or long-horizon enterprise workflows.
- You need expert preference data in many languages.
- You want robotics demonstrations from the same supplier (Terra).
Choose Scale AI when…
- Your roadmap includes LiDAR, infrared or video labeling.
- You need FedRAMP or work with government buyers.
- You want SEAL-style launch evaluations.
Pricing model
Both sell through sales teams. Labelbox did not show a public price list when we checked on 2026-11-09. Scale books work through demos and custom contracts. Our pricing guide lists every vendor's buying model.
FAQ
Is Labelbox still a labeling tool?
Labelbox now leads with RL environments (Horizon), an expert network (Alignerr), robotics data (Terra) and Recursion agents for engineering and research teams. It is both a data provider and software.
Which is better for computer-use agents?
Labelbox explicitly offers computer-use environments, and its WorldSim mirrors enterprise toolchains. Scale offers RLHF and evaluation and says it is moving toward more realistic RL training.
Which has more certifications?
Scale lists SOC 2, ISO 27001 and FedRAMP. Labelbox states SOC 2 Type II for Alignerr.
Keep comparing
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Reviews: Scale AI review · Labelbox review. More: full ranking, alternatives to Scale AI, how to choose a provider.
Sources
- Labelbox home page
- Labelbox Horizon
- Alignerr expert network
- Labelbox and Meta GIM
- Scale AI home page
- Scale Data Engine
- Scale Generative AI Data Engine
- Scale: Building for 2026
- Scale on Meta's investment
- Scale's new CEO
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