Peek operates a SaaS platform serving the experiences industry with booking, operations, and guest management tools. The stack reveals a modern, distributed architecture—Java and Elixir backends on Kubernetes, GraphQL APIs, and a data layer built on Airflow + Airbyte + BigQuery + dbt. Current project activity centers on agent orchestration and AI-assisted booking flows, while pain points around data reliability and AI-driven bugs suggest the company is actively scaling AI features into production and wrestling with data quality as a core bottleneck.
Peek provides an operating system for the experiences industry—museums, attractions, tours, and activities. The platform handles ticketing, reservations, guest experiences, and merchant operations. Founded in 2011 and headquartered in San Francisco, the company operates at mid-market scale (201–500 employees) with a focus on AI-powered tools to increase merchant revenue and streamline operations. Current hiring is concentrated in engineering and data roles, with senior-level positions dominating the active pipeline—indicating expansion of core technical capacity and data infrastructure.
Peek's stack spans Java and Elixir for backend services, JavaScript/TypeScript for frontends, Kubernetes for orchestration, AWS (EKS, RDS, Aurora, ElastiCache, BigQuery) for cloud infrastructure, and a modern data pipeline (Airflow, Airbyte, dbt, BigQuery, Looker).
Active projects include agent orchestration systems, AI-assisted booking flows, embeddable scheduling widgets, B2B/B2C sales tooling, and internal analytics pipelines. Recent focus areas are greenfield booking redesign and AI data serving layer architecture.
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Peek'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.