Scale AI is a data infrastructure company that provides high-quality training data, evaluation tools, and AI platform capabilities for organizations building and deploying artificial intelligence systems. Founded in 2016 by Alexandr Wang and Lucy Guo, the company is headquartered in San Francisco, California, and has grown into one of the most prominent AI data companies with a valuation exceeding $13 billion. Scale AI began as a data labeling service, providing human-annotated training data for machine learning models, and has expanded into a comprehensive AI platform serving both commercial enterprises and government customers. The company's core data labeling services cover a wide range of AI use cases including computer vision annotation for autonomous vehicles and robotics, natural language processing data for text classification and entity recognition, audio transcription and annotation, and reinforcement learning from human feedback (RLHF) data for training large language models. Scale has played a significant role in the development of many major AI systems, providing training data to leading AI companies. The Scale Generative AI Platform provides tools for enterprises to develop, evaluate, and deploy LLM-powered applications. This includes Scale Data Engine for curating and managing fine-tuning datasets, Scale GenAI Platform for building and testing AI applications, and Scale Evaluation for benchmarking model performance. The SEAL Leaderboard, maintained by Scale AI, provides independent benchmarks for comparing large language model capabilities. Scale also serves the U.S. Department of Defense and intelligence community through its Scale Donovan platform, which provides AI capabilities for government applications. Scale AI pricing is typically custom and contract-based, tailored to the specific data volume, annotation complexity, and platform requirements of each customer. The company employs a global network of human annotators alongside AI-assisted labeling tools to deliver training data at scale.

AI Data Analysis

Scale AI provides data analysis capabilities through its Generative AI Platform and evaluation tools. The platform enables organizations to analyze model performance, assess data quality, benchmark AI systems through the SEAL Leaderboard, and derive insights from complex datasets used in machine learning development and deployment.

AI MLOps Tools

Scale AI supports ML operations through its data engine for managing training data pipelines, model evaluation tools for benchmarking performance, and platform capabilities for testing and deploying AI applications. These tools address the data-centric aspects of MLOps, ensuring model quality through high-quality training data and rigorous evaluation.

AI Model Hosting

Scale AI's Generative AI Platform enables enterprises to build, test, and deploy LLM-powered applications with tools for prompt engineering, model evaluation, fine-tuning data management, and application development. The platform supports the full lifecycle from model selection and customization through production deployment and monitoring.

AI Research Tools

Scale AI contributes to AI research through its SEAL Leaderboard for independent model benchmarking, evaluation frameworks for assessing LLM capabilities, and training data infrastructure used by leading AI research labs. The company's annotation services have supported the development of many significant AI models and research breakthroughs.

AI Training Platforms

Scale AI is one of the largest providers of training data for AI systems, offering human annotation services for computer vision, NLP, audio, and RLHF data used to train foundation models and specialized AI systems. The company provides data labeling at scale with quality assurance, enabling organizations to build high-performing models with accurately labeled training datasets.