Scale AI
Enterprise AI data platform providing high-quality training data through human-in-the-loop labeling, synthetic data generation, and RLHF services
$14B
Valuation
400+
Enterprise Customers
1B+
Labels Delivered
Overview
Scale AI is the leading enterprise data labeling platform powering AI development at companies like OpenAI, Meta, Microsoft, and the US Department of Defense. Founded by Alexandr Wang (who became the youngest self-made billionaire), Scale combines a global workforce of expert annotators with AI-assisted tooling to deliver high-quality training data for computer vision, NLP, and generative AI. Their RLHF (Reinforcement Learning from Human Feedback) services have been instrumental in training frontier LLMs, while their Donovan platform serves government and defense AI applications.
The Verdict
Who Should Use Scale AI?
Best For
- Frontier AI labs training LLMs
- Autonomous vehicle companies
- Government/defense AI projects
- Enterprises needing high-volume labeling
- Teams requiring RLHF pipelines
Not Ideal For
- Startups with limited budgets
- Small datasets (< 10K samples)
- Self-service DIY labeling needs
- Projects needing instant turnaround
What's Great
- Industry-leading quality and accuracy
- Massive scale (billions of labels delivered)
- Expert annotators for specialized domains
- Strong security for sensitive data (FedRAMP)
- End-to-end RLHF pipeline support
- Proven with frontier AI labs (OpenAI, Meta)
Watch Out For
- Enterprise pricing (no public pricing)
- Long sales cycles for new customers
- Minimum project sizes required
- Less suitable for small teams
- Turnaround times vary by project complexity
Pricing
Starter
Custom
Small projects, basic annotation types
Growth
Custom
High-volume labeling, dedicated support
Enterprise
Custom
Full platform, SLA, compliance
Government
Contract
FedRAMP, defense, classified data
View all features & details
Data Labeling Types
- Image annotation (bounding boxes, segmentation)
- Video annotation (tracking, temporal)
- 3D point cloud labeling (LiDAR)
- Text annotation (NER, classification)
- Audio transcription & labeling
- Document understanding
- Conversational AI data
GenAI Services
- RLHF (Reinforcement Learning from Human Feedback)
- Prompt engineering data
- Red teaming & safety evaluation
- Model evaluation & benchmarking
- Synthetic data generation
- Instruction tuning data
Platform Features
- Scale Nucleus - Data management
- Scale Rapid - Fast annotation API
- Scale Studio - Labeling interface
- Quality assurance workflows
- Multi-stage review pipelines
- Custom ontology support
Compliance & Security
- SOC 2 Type II
- ISO 27001
- FedRAMP (Government)
- HIPAA capable
- On-premise deployment options
- Data residency controls
Key Products
Scale Data Engine
- Core labeling platform
- AI-assisted annotation
- Expert workforce management
- Quality control automation
Scale Donovan
- Defense & government AI
- Classified data handling
- Mission-critical applications
- FedRAMP authorized
Scale GenAI Platform
- RLHF data pipelines
- LLM evaluation tools
- Fine-tuning datasets
- Safety testing data
Company Background
Funding & Valuation
- $14B valuation (2024)
- $1B+ total funding raised
- Investors: Accel, Tiger Global, Index
- Founded by Alexandr Wang (2016)
Key Customers
- OpenAI - LLM training data
- Meta - AI research
- Microsoft - Azure AI
- US Department of Defense
- Toyota, GM, Waymo - AV data
How It Compares
| Feature | Scale AI | Labelbox | Snorkel AI |
|---|---|---|---|
| Primary Model | Managed workforce | Self-serve platform | Programmatic labeling |
| RLHF Support | Full pipeline | Basic | Limited |
| Enterprise Focus | Core strength | Growing | Enterprise |
| Government/Defense | FedRAMP, DoD | Limited | No |
| Self-Service | Limited | Strong | Yes |
| Pricing Transparency | Enterprise only | Published tiers | Enterprise |
| Best For | Frontier AI labs | Mid-market teams | Weak supervision |
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