Scale AI develops AI software and data infrastructure that helps organizations build reliable AI systems from training through deployment and oversight. Its business spans high-quality data generation and annotation, model evaluation, fine-tuning, generative AI application development, and specialized workflows for public sector, autonomy, and robotics use cases. The company’s core position is in turning raw or fragmented data into production-ready inputs, evaluations, and applications for demanding AI programs.
Scale AI serves frontier AI labs, enterprises, and governments that need stronger model performance, safety, and operational reliability. Its portfolio combines data engines, application-building tools, dataset management, and domain-specific platforms so customers can improve models, launch AI applications in secure environments, and manage AI systems in production. The company also extends into evaluation and research-led capabilities that support model benchmarking, testing, and responsible deployment.
Offerings, Capabilities, and Integrations
Scale AI’s offerings center on the infrastructure required to make AI usable in production. Its capabilities include data collection, curation, annotation, reinforcement learning and human feedback workflows, dataset management, model testing and evaluation, retrieval-augmented generation, agent development, and deployment tooling for secure enterprise and government environments.
The company supports multimodal AI workflows across text, image, video, lidar, geospatial, and robotics data. Its platforms are designed to work with both open and closed models, connect to enterprise data sources, and run in customer-controlled cloud environments. Scale AI also layers in governance, monitoring, benchmarking, and human-in-the-loop review to help customers improve quality, safety, and trust as AI systems move from experimentation into operational use.
Products and Services
- Scale Data Engine: Scale AI’s core data infrastructure platform for collecting, curating, annotating, evaluating, and optimizing high-quality data used to train and improve AI models across generative AI, computer vision, and machine learning workflows.
- Scale GenAI Platform: A full-stack platform for building, testing, evaluating, deploying, and monitoring enterprise generative AI applications using proprietary data, with support for APIs, SDKs, agent workflows, and secure cloud deployment.
- Scale Donovan: A public-sector generative AI and decision-support platform built for defense, intelligence, and civilian government users to search large data holdings, operationalize AI agents, and accelerate mission workflows in secure environments.
- Nucleus: A dataset management platform that brings together data, labels, and model predictions so machine learning teams can debug models, curate datasets, and improve data quality.
- Scale Pro: A managed data platform for AI-enabled businesses that combines API-based task submission, customized project setup, high-volume labeling operations, and SLA-backed delivery for complex data workflows.
- Physical AI Data Engine: Scale AI’s data collection and annotation offering for robotics and physical AI programs, built to generate large, diverse, multimodal datasets for training real-world robotic and embodied AI systems.
- Automotive Data Engine: A data engine for autonomous driving and autonomy programs that supports 2D and 3D labeling, sensor-fusion workflows, data curation, and model evaluation for automotive development.
- Scale Evaluation: An evaluation offering that helps customers measure AI model and application performance, safety, and reliability using benchmarks, human review, red teaming, and analysis tools.
- Defense Llama: A purpose-built large language model for U.S. national security use cases, customized for defense workflows and available within Scale Donovan in controlled government environments.
Target Customers
Scale AI targets frontier model developers and AI labs that need expert-generated data, RLHF workflows, and evaluation infrastructure to train, test, and improve advanced models. It also serves enterprise teams building production AI applications, especially organizations that need custom models, agentic workflows, retrieval over proprietary data, and stronger controls around quality and deployment.
The company has a strong fit with government and national security organizations that require secure, auditable AI systems for mission-critical workflows. It also addresses domain-specific builders in autonomy and robotics, including automotive and physical AI teams, as well as enterprises with complex, document-heavy, or regulated environments such as healthcare and life sciences.
Cloud Integrations and Marketplace
- AWS Marketplace: Scale AI has an AWS Marketplace seller presence with listings for products including Scale GenAI Platform and Scale Donovan, supporting procurement and deployment on AWS environments.
- Azure Marketplace: Scale AI offers Scale GenAI Platform through Azure Marketplace and positions the platform for deployment in Microsoft Azure customer environments.
- Google Cloud Platform: Scale AI documentation for Scale GenAI Platform includes GCP deployment and infrastructure support, indicating compatibility with Google Cloud customer environments even without a verified marketplace listing.
Key People
- Jason Droege: Interim Chief Executive Officer
- Alexandr Wang: Founder and Director
- Arun Murthy: Chief Product & Technology Officer
- Vijay Karunamurthy: Field CTO
- Dan Tadross: Head of Public Sector
- Bing Liu: Head of Research
Key Facts
- Headquarters: San Francisco, California, United States
- Employees: More than 1,000
- Annual Revenue: Approximately $870 million
- Parent Company: None
- Subsidiaries: ICG Solutions
- Publicly Listed: Privately held
Analyst Recognitions
- Gartner: 2022 Gartner Cool Vendors in Data-Centric AI – Cool Vendor.
