Human data infrastructure for AI model training and evaluation
SuperAnnotate operates a managed annotation and evaluation platform with a distributed network of human experts. The tech stack is developer-oriented (Python, JavaScript, TypeScript, Node.js, PostgreSQL, AWS primitives) and built for scale—RabbitMQ and Redis handle async workflows, Terraform/CDK for infrastructure-as-code. Hiring is skewed senior (5 of 7 roles) across engineering, data, and go-to-market functions, paired with active projects around data pipeline architecture, self-serve infrastructure, and talent acquisition—revealing an organization scaling both product depth and revenue operations simultaneously while managing rapid growth complexity.
SuperAnnotate provides a platform for annotating, evaluating, and generating training data for AI model development. The service combines a vetted network of remote annotation experts with proprietary workflows and tooling designed for complex, high-value AI data projects. The company serves AI development teams at mid-market and enterprise scale, particularly those building or fine-tuning large language models and generative AI systems. Operations span the United States and Armenia, with a 51–200-person team headquartered in San Francisco.
Python, JavaScript, TypeScript, Node.js, PostgreSQL, AWS (Lambda, RDS, CDK), Next.js, Terraform, RabbitMQ, Redis, Prisma, and TypeORM for backend and infrastructure. OpenAI and Anthropic APIs are integrated.
Headquartered in San Francisco, California. Active hiring in the United States and Armenia.
SuperAnnotate's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.