Expert network platform supplying vetted domain expertise, including AI evaluation
Office Hours runs an on-demand expert network that matches vetted specialists with client organizations through calls, surveys and AI interviews. Research is the largest hiring function, and projects center on AI model evaluation for biology and immunology problems, pointing to a push into expert-sourced AI training and evaluation data. A Kubernetes stack on AWS EKS with Argo CD, Flux and Temporal reflects a mature, GitOps-driven platform team.
Notable leadership hires: Head of Marketing
Office Hours operates an expert network platform that connects organizations with vetted specialists across industries, functions and niche domains. Experts share knowledge through live calls, surveys and AI interviews, while the platform handles matching and payments. Clients span technology, life sciences, investment, consulting and AI organizations. Founded in 2020 and privately held, the company is headquartered in San Francisco with teams in New York and Bangalore, and has 51–200 employees.
Office Hours runs on AWS EKS and Kubernetes with Terraform, Helm, Argo CD and Flux, using Python, Go, Node.js and TypeScript, PostgreSQL, MongoDB Atlas, OpenSearch, Temporal, React/Next.js, and Swift for iOS.
Yes. Research is the largest hiring area, focused on AI evaluation of biological and immunology problems, alongside engineering, sales and finance roles, mostly at senior level in the United States.
Current projects include AI model evaluation on biology and immunology problems, AI-powered product capabilities, an in-house accounting function with internal controls, and mobile standards and tooling.
Other companies in the same industry, closest in size
Office Hours'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.