Can I use Scale's platform with my own in-house annotation team?

Yes, the self-serve 'Bring Your Own Workforce' tier allows you to use Scale's tooling and management UI with your own annotators. The enterprise tier offers a managed workforce or a hybrid model.

How does Scale ensure data labeling quality?

They combine ML-powered pre-labeling with a multi-stage human-in-the-loop review process, quality metrics, and dedicated operations support for enterprise clients to achieve high-accuracy ground truth data.

Is there a free tier or trial?

The self-serve Data Engine offers a free tier: the first 1,000 labeling units (e.g., text segments, image polygons) and 10,000 images for data management are free to get started.

What types of data can be annotated?

Scale supports a wide range: text (NLP, LLM), images (computer vision), video, LiDAR/3D point clouds (autonomy), and documents. Custom data types are handled via their enterprise API.

How does the API integration work for custom pipelines?

Scale provides REST APIs to create projects, upload tasks, manage annotations, and download results. You can integrate these endpoints into your own data pipelines, CI/CD, and model training scripts for automation.

What are the data security and compliance standards?

Enterprise deployments offer SOC 2 compliance, data encryption, IP allowlisting, and options for on-premise or VPC deployment for sensitive data (e.g., classified government data). The self-serve tier is cloud-based.

Directory/Search/Data Platform/Scale AI

Scale AI

Scale AI provides the data infrastructure and end-to-end AI platform for training, evaluating, and deploying mission-critical AI systems. Its core offering is the Data Engine, a platform for high-quality data annotation and management, used by leading AI labs like OpenAI and Meta to train frontier models. Beyond data, Scale offers an enterprise GenAI platform for building custom applications and a defense-focused product, Donovan, for intelligence analysis. The platform combines ML-powered pre-labeling with human-in-the-loop review to deliver training data at scale. It serves enterprise, government, and research customers across sectors like defense, healthcare, robotics, and energy, providing the foundational data layer that AI systems rely on for performance and reliability.

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Sep 22, 2026

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Enterprise AI SystemsData Annotation PlatformGenAI PortfolioBYOW AnnotationNucleus Data ManagementModel Benchmarking

Product information

Everything worth knowing about Scale AI

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

AI System Development & Deployment

Build and own enterprise AI systems, finding the right use case and managing the outcome. Includes agentic solutions for various industries.

Data Engine for Model Training

Provides high-quality, frontier-grade data for training AI models. Features sourced contributors (25% with advanced degrees) and precision sourcing.

Enterprise GenAI Portfolio

Transform data into customized, enterprise-ready Generative AI applications. Includes tools for data annotation and management.

Data Annotation & Curation

Self-serve platform for annotating and managing data for ML projects. Includes Bring Your Own Workforce (BYOW) annotation and Nucleus data management.

Technical capabilities

ML-Powered Pre-Labeling & Human Review

Combines machine learning powered pre-labeling with active tooling and configurable levels of human review to turn raw data into training data.

Benchmarking & Leaderboards

Runs private benchmarks and leaderboards for AI companies to measure and improve model capabilities (e.g., SWE-Bench Pro for agentic coding).

Must watch videos

Who uses it

Real use cases, no hype

Training Data for LLMs

Source and annotate high-quality, human-labeled data to train and fine-tune large language models and generative AI systems.

Autonomous Vehicle Development

Label sensor data (LiDAR, camera) with precision for perception model training in self-driving cars and robotics.

Healthcare AI

Annotate medical records, imaging, and clinical data to build diagnostic and administrative AI tools.

Defense & Intelligence

Process classified and open-source data to generate actionable intelligence for national security applications.

Physical AI & Robotics

Generate real-world training data for robotic manipulation, navigation, and foundation model development.

Enterprise Document Processing

Extract and structure data from complex documents (insurance, legal) to power AI-driven automation.

Model Evaluation & Benchmarking

Use Scale's Leaderboards to run private benchmarks and rigorously evaluate frontier model capabilities.

What's great

Enterprise-grade data labeling and annotation platform
Powers training data for frontier AI models (Meta, Cohere, etc.)
Full-stack offering: Data Engine + GenAI Platform
Strong public sector and defense contracts (CDAO, BAE Systems)
Self-serve option with free tier for experimentation
Specialized in high-stakes domains: healthcare, autonomy, robotics

Technical strengths

Proprietary Data Engine with ML-powered pre-labeling and human-in-the-loop QA

Where it falls short

Pricing opaque; requires demo for enterprise quotes
Steep learning curve for full platform integration
Primarily enterprise-focused; overkill for small projects
Self-serve tier limited to 1k labeling units / 10k images free

Technical limitations

API and data ingestion can be complex for custom workflows
May require significant internal resources to manage Scale-led annotation
Vendor lock-in risk for proprietary data pipelines and tools

For technical folks

The deep-dive specs

FAQ

Includes technical Q&A

The Data Engine focuses on raw data annotation, curation, and management for ML training. The GenAI Platform is an application layer for building, fine-tuning, and deploying enterprise-ready generative AI applications on top of that data.