Scale AI
To develop reliable AI systems for the world's most important decisions by delivering proven data, evaluations, and outcomes to AI labs, governments, and the Fortune 500.
At a Glance
- AI labs and frontier model developers
- Fortune 500 enterprises
- U.S. Government and Defense (DoD, intelligence agencies, military commands)
- International governments (Qatar, Saudi Arabia, UAE)
- +9 more
AI Tools by Scale AI
(1)Scale AI
AI Data Labeling and Evaluation
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Latest News
Scale AI sues Department of Defense - lawsuit filed January 30, 2026 with case documents expected to include classified information
Scale AI and malomatia sign three-year MoU to deliver sovereign AI capabilities for Qatar
Meta acquires 49% stake in Scale AI for $14.8 billion, valuing company at over $29 billion; Alexandr Wang joins Meta as Chief AI Officer, Jason Droege named CEO
Scale AI signs five-year partnership with Qatar government to develop national AI infrastructure across education, healthcare, civil service, transportation, and tourism
Products & Services
Data annotation, collection, and curation platform that combines automation and human intelligence to rapidly generate high-quality training data tailored to specific AI goals. Features include finding, categorizing, and fixing model failures, and optimizing labeling spend with curated data.
Platform for creating tailored training datasets curated by experts, integrating automation and human intelligence for goal-specific training data. Includes RLHF integration, model evaluation, red-teaming, and responsible development framework focused on privacy, fairness, transparency, and ethics.
Full-stack solution to build, evaluate, train, and scale reliable AI agents and applications. Features include agent execution with enterprise-grade hosting and orchestration, advanced RAG tools, agent operations with telemetry and data management, enterprise-ready infrastructure supporting deployment on AWS/Azure/GCP, and model and data flexibility with major closed and open-source models.
AI platform designed for public sector and classified government environments. Provides agentic solutions for defense and intelligence with security compliance (FedRAMP, ISO, AICPA SOC). First LLM deployed on classified military networks.
Market Position
Scale AI positions itself as the leading data infrastructure and evaluation platform for AI, differentiating through: (1) Enterprise-grade data quality with expert human-in-the-loop validation, (2) Full-stack AI platform from data to deployment, (3) Strong government and defense focus with classified network capabilities, (4) Partnerships with all major AI model providers (OpenAI, Google, Meta, Cohere), (5) Proprietary evaluation benchmarks through SEAL. Main competitors include Labelbox, Appen, Supervisely, and Alegion in data labeling, but Scale's broader platform approach and government/enterprise focus creates differentiation.
Leadership
Founders
Alexandr Wang
Born in 1997 in Los Alamos, New Mexico, son of Chinese immigrant physicists. Math Olympiad qualifier (2013) and US Physics Team member (2014). Attended MIT at age 17 studying mathematics and computer science but dropped out after freshman year. Previously worked as Software Engineer at Addepar, Tech Lead at Quora, and Algorithm Developer at Hudson River Trading. Founded Scale AI at age 19.
Lucy Guo
Computer science college dropout from Carnegie Mellon University where she studied computer science and human-computer interactions. Became a Thiel Fellow. Co-founded Scale AI in 2016 at age 21. Left the company in 2018 following a falling out with co-founder Alexandr Wang, retaining approximately 3% ownership.
Executive Team
Jason Droege
CEO (Interim, appointed June 2025)
Former Chief Strategy Officer at Scale AI. Previously Venture Partner at Benchmark working with early-stage founders. Former Uber executive.
Alexandr Wang
Board Member (former CEO until June 2025, now at Meta as Chief AI Officer)
Founder and former CEO. Math Olympiad qualifier and US Physics Team member. MIT dropout. Previously worked at Quora, Addepar, and Hudson River Trading. Joined Meta in June 2025 while remaining on Scale's Board.
Board of Directors
Founding Story
Founded in June 2016 when Alexandr Wang was 19 years old. The concept originated from a personal project where Wang tried to build a camera system for his refrigerator to track groceries and realized the primary obstacle was lack of sufficient data to train the AI model. Wang and Lucy Guo initially gained traction by pitching their solution at the Computer Vision and Pattern Recognition conference. The vision was to create the 'data infrastructure to power the AI revolution,' addressing the critical bottleneck in AI development: the need for massive amounts of accurately labeled data through a combination of machine learning and human oversight.
Business Model
Revenue Model
Enterprise subscriptions and usage-based pricing for API services, data labeling, model evaluation, and custom AI solutions. Government contracts for defense and intelligence applications. No public pricing tiers - all pricing determined through enterprise sales process.
Target Markets
- AI labs and frontier model developers
- Fortune 500 enterprises
- U.S. Government and Defense (DoD, intelligence agencies, military commands)
- International governments (Qatar, Saudi Arabia, UAE)
- Autonomous vehicle companies
- Healthcare organizations
- Training and fine-tuning large language models
- Defense and intelligence decision advantage
- Enterprise AI transformation and automation
- Model safety and alignment research
- Autonomous vehicle data labeling
- Computer vision model training
- OpenAI
- Microsoft
- Meta Platforms