What is Scale?
Scale is the backbone of modern AI development, providing the high-quality data infrastructure that powers the world's most advanced models. From startups to government agencies, teams rely on Scale's Data Engine to curate, annotate, and evaluate the training data that makes AI reliable. With native Reinforcement Learning from Human Feedback...
How to Use Scale
Scale's Data Engine makes it easy to prepare high-quality training data for your AI models. Follow this guide to annotate your first dataset.
1
Sign up for a Scale account
Visit scale.com and create a free account. You'll get access to the self-serve Data Engine dashboard where you can manage your annotation projects.
2
Upload your data
Upload images, text, or audio files directly through the dashboard. Scale supports common formats like JPEG, PNG, CSV, and JSON.
3
Configure annotation tasks
Define labeling instructions, choose annotation types such as bounding boxes or text classification, and set quality thresholds to ensure accuracy.
4
Review and export annotations
Monitor annotation progress in real-time, review individual results for quality, and export your labeled dataset in your preferred format for model training.
Scale Core Features
High-quality data annotation services for text, image, video, and audio
Reinforcement Learning from Human Feedback (RLHF) for LLM fine-tuning
Comprehensive model evaluation and benchmarking suites
Red-teaming for adversarial testing and safety validation
Full-stack AI system integration and deployment support
Self-serve Data Engine with pay-as-you-go pricing model
Custom enterprise-ready Generative AI application development
Data curation, image upload, and annotation management
Dedicated customer operations support for enterprise clients
Enterprise-grade quality SLAs and security compliance
Scale Use Cases
- 1Training and fine-tuning large language models with high-quality human feedback and RLHF to improve accuracy, safety, and domain-specific performance.
- 2Building custom generative AI applications for enterprise workflows, leveraging Scale's platform to develop, deploy, and monitor tailored AI solutions.
- 3Model evaluation and safety testing using red-teaming and benchmarking to identify vulnerabilities, bias, and reliability issues before production deployment.
- 4Data curation for computer vision projects by uploading and managing large image datasets with optimized annotation spend and quality control.
- 5Enterprise AI governance and oversight, providing audit trails, compliance documentation, and robust security for regulated industries.
Pros and Cons of Scale
Pros
- Comprehensive end-to-end data infrastructure covering annotation, RLHF, evaluation, and red-teaming under one platform, reducing vendor management overhead.
- Generous free tier with 1,000 free labeling units and 10,000 free images, allowing teams to evaluate the platform without upfront investment.
- Enterprise-grade support with dedicated operations team, custom SLAs, and stringent quality guarantees that ensure reliability for mission-critical AI.
- Proven track record with over $1 billion paid to contributors and 15 billion human decisions, demonstrating massive scale and deep experience.
✕ Cons
- Enterprise pricing is custom and can be prohibitively expensive for smaller teams or startups with limited budgets.
- Platform complexity and breadth of features create a steep learning curve that may require specialized expertise to fully leverage.
- Lack of transparent pricing for the pay-as-you-go tier beyond the free allowance makes it difficult to estimate costs for larger annotation projects.
Scale vs Top Alternatives
| Feature | Labelbox | Appen | Amazon SageMaker Ground Truth |
|---|---|---|---|
| Data Annotation Quality | AI-assisted annotation with quality workflows | Crowdsourced annotations with managed workforce | Built-in annotation with AWS ecosystem |
| RLHF Support | Limited RLHF via third-party integration | RLHF available as add-on service | No native RLHF support |
| Model Evaluation & Red-Teaming | Basic model evaluation tools | Model evaluation services available | Limited evaluation features |
| Enterprise Security & SLAs | Enterprise security and compliance | Enterprise-level security options | AWS enterprise security |
Scale Pricing
Free tier available — no credit card required
Free Tier
$0/month
- Free first 1,000 labeling units
- Free first 10,000 images
- Access to self-serve Data Engine
Enterprise
Custom/month
- Dedicated customer operations support
- Enterprise-grade quality and SLAs
- Customized enterprise-ready Generative AI applications
- Full-stack AI system integration
Scale FAQ
What is Scale?+
Scale is a data platform that provides high-quality training data, RLHF, model evaluation, and full-stack AI infrastructure for building reliable AI applications.
Does Scale offer a free tier?+
Yes, the self-serve Data Engine includes a free tier with 1,000 free labeling units and 10,000 free images.
How does Scale's pricing work?+
Scale offers pay-as-you-go pricing for the self-serve Data Engine and custom pricing for enterprise plans with dedicated support and SLAs.
What types of data annotation does Scale support?+
Scale supports image, video, text, and audio annotation, as well as RLHF, model evaluation, and red-teaming.
Can Scale be used for government projects?+
Yes, Scale provides enterprise-grade security and compliance for government and regulated industries.
How does Scale ensure data quality?+
Scale uses a combination of automated quality checks, human review, and dedicated project managers to maintain high annotation accuracy.
How do I get started with Scale?+
You can sign up for the self-serve Data Engine on Scale's website and start uploading data immediately.
Scale Review — Editor's Score
Who Should Use Scale?
Enterprises and government agencies building mission-critical AI applications, as well as AI researchers and developers needing high-quality training data for fine-tuning and evaluation.
8.8
Overall Score
Functionality
9
Ease of Use
7
Value for Money
8
Support
8
Scale is an indispensable platform for any organization serious about building reliable, high-quality AI. Its combination of data annotation, RLHF, and model evaluation under one roof is unmatched, though smaller teams may find the enterprise pricing out of reach. The generous free tier makes it easy to start, but scaling can get costly. Overall, Scale sets the standard for AI data infrastructure.
- End-to-end platform for data annotation, RLHF, and evaluation
- Generous free tier with 1,000 free labeling units
- Enterprise-grade security and compliance
- Proven at massive scale with $1B+ paid to contributors
Review by BuzzWithAI Editorial Team • 2026-06-06T09:40:54.935Z
📺 Scale Tutorials & Introduction
Upgrading Your Fleet into an AV Data Engine - Scale AI - YouTube
Best AI tool for blogging – Content at Scale (full tutorial) - YouTube
How to Train, Deploy & Scale AI Models with Lightning AI - YouTube
Keywords:
#data annotation#RLHF#model evaluation#red-teaming#AI training data#generative AI#enterprise AI#data engine#machine learning#AI infrastructure#human feedback#AI safety