Scale.com is an enterprise-grade AI infrastructure platform that supports organizations in building, training, and deploying high-quality AI models. From autonomous vehicles to generative AI, Scale empowers teams by delivering labeled data, synthetic datasets, and model evaluation services to support the entire machine learning lifecycle.
Founded in 2016, Scale has grown to become a foundational platform for the world’s top AI teams and government agencies. The company combines cutting-edge tools with a large, managed workforce to ensure highly accurate annotations and scalable data pipelines. Whether you’re training a large language model or developing AI for defense, Scale provides the secure infrastructure and human expertise needed to ship models to production faster and more reliably.
Features
1. Data Labeling Services
Scale offers industry-leading data annotation services for images, videos, text, LiDAR, audio, and documents. Labeling is enhanced with human-in-the-loop processes and AI-powered quality assurance.
2. Synthetic Data Generation
Generate simulated datasets for edge-case scenarios and underrepresented data. Especially valuable for autonomous vehicles and robotics, synthetic data enables robust training for rare real-world events.
3. RLHF (Reinforcement Learning with Human Feedback)
Supports the development and fine-tuning of large language models by using human feedback to align model outputs with user intent.
4. Scale Nucleus
A powerful dataset management and model evaluation platform. It helps users visualize failure cases, debug models, and improve dataset quality with insights derived from performance metrics.
5. Secure Model Deployment
Scale provides APIs and infrastructure for model inference, real-time serving, and post-deployment evaluation. Models can be monitored continuously to identify drift and bias.
6. Multi-Modal and Industry-Specific Support
Scale supports a wide array of formats and use cases—text, image, video, 3D point clouds, geospatial imagery—tailored to industries like defense, automotive, healthcare, and finance.
How It Works
Scale.com’s workflow is structured to streamline and accelerate the AI development process:
Step 1: Define Data Needs
Clients identify the data types, annotation formats, or synthetic environments required. Scale works closely to scope the project.
Step 2: Upload or Generate Data
Users upload raw data or request synthetic datasets tailored to specific use cases.
Step 3: Annotation or Generation
Scale’s platform and workforce perform labeling, synthetic data creation, or feedback collection. Quality assurance mechanisms are integrated into every step.
Step 4: Evaluate with Nucleus
After labeling or training, users can evaluate model performance on curated datasets and refine data inputs based on insights.
Step 5: Deploy and Monitor
Models are served via API endpoints with built-in monitoring for performance tracking, bias detection, and drift analysis.
Use Cases
Autonomous Vehicles
Label LiDAR, camera, and radar data. Generate synthetic driving scenes to train perception and planning models.
Government and Defense
Analyze satellite imagery, ISR data, and geospatial intelligence with secure, air-gapped infrastructure.
Large Language Models (LLMs)
Collect human feedback to fine-tune LLMs using RLHF. Annotate diverse text datasets for pretraining and alignment.
Retail and E-Commerce
Power recommendation systems and product search through high-quality visual and textual annotations.
Healthcare
Label radiology scans, pathology slides, and transcriptions for medical imaging and diagnostics AI.
Financial Services
Extract structured data from financial documents and automate compliance workflows with NLP.
Pricing
Scale.com operates on a custom pricing model based on:
Data type (e.g., text, video, LiDAR)
Annotation complexity
Volume of data
Turnaround time
Additional services like synthetic data or RLHF
Compliance and security requirements
There are no fixed public pricing tiers. Prospective clients must contact the Scale team to request a quote or schedule a custom demo via the Scale Contact Page.
Strengths
Comprehensive AI Data Platform
Supports the entire AI development lifecycle—from data curation to model deployment.
High Annotation Accuracy
Combines human annotators with automated QA systems for consistent, high-quality data.
Scalable Infrastructure
Capable of managing massive data volumes and complex workflows at enterprise scale.
Versatile Data Modalities
Supports a wide range of data types including image, video, LiDAR, audio, and documents.
Synthetic Data Capabilities
Enables simulation of rare or difficult-to-capture scenarios, enhancing model robustness.
Trusted by Industry Leaders
Used by OpenAI, Meta, Toyota, the U.S. Department of Defense, and other leading organizations.
Drawbacks
No Public Pricing
Requires direct sales contact for cost information, which may be a barrier for smaller teams or independent developers.
Primarily Enterprise-Focused
Designed for large-scale projects and institutions, not optimized for hobbyists or small startups.
Limited Self-Serve Options
Scale’s services are largely managed and customized, with fewer plug-and-play tools for individual use.
Higher Cost for Premium Services
Advanced offerings like RLHF, synthetic data, and model deployment come at a premium.
Comparison with Other Tools
Labelbox focuses more on self-serve labeling with a flexible UI but lacks integrated tools like RLHF or synthetic data generation.
SuperAnnotate offers collaborative labeling tools for teams but does not provide the same level of infrastructure for model evaluation and deployment.
AWS SageMaker Ground Truth integrates with AWS services but offers less customization and quality assurance than Scale’s human-in-the-loop approach.
Snorkel AI emphasizes programmatic labeling and weak supervision, ideal for certain academic and NLP workflows but less versatile across data types.
Scale.com stands out for its turnkey, end-to-end solution that scales across industries and supports both real and synthetic data pipelines with expert human feedback mechanisms.
Customer Reviews and Testimonials
Scale has earned endorsements from high-impact AI leaders and government partners:
“We’ve used Scale to support the training of some of our largest language models. Their data quality is unmatched.” – Lead Researcher, Generative AI Lab
“Scale’s synthetic data platform enabled us to prepare for critical edge cases we couldn’t capture in the real world.” – Director, Autonomous Systems
“Using Nucleus, we identified failure cases in our production model that we would have otherwise missed. It’s a game-changer.” – Head of ML Ops, Fortune 500 Company
“Scale was instrumental in helping us build secure, compliant pipelines for satellite image analysis in defense applications.” – CTO, Defense Contractor
Conclusion
Scale.com is a mission-critical platform for organizations building cutting-edge AI systems. By combining expert data annotation, synthetic data capabilities, human feedback loops, and model evaluation tools, Scale helps teams deliver more accurate, reliable, and production-ready models—faster.
Whether you’re a Fortune 500 company, an autonomous vehicle startup, or a national defense agency, Scale.com delivers the AI data infrastructure you need to succeed.
