Live event point-of-sale platform handling 125,000+ events annually
atVenu operates a transaction-processing platform purpose-built for live events, handling venues, festivals, and sporting events at scale. The tech stack reveals a mature full-stack operation: Ruby/Rails + React + PostgreSQL + Redis on AWS, with payment integration (Stripe) and offline-capable architecture. Active hiring is engineering-heavy (5 of 7 roles), concentrated in mid to senior levels, while a parallel compliance push signals maturation toward enterprise compliance — privacy-by-design and data protection assessments are live projects, reflecting either new regulatory requirements or customer-driven demands.
atVenu is a live event commerce platform managing point-of-sale, ticketing, and inventory for large-scale events. The platform processes transactions across 125,000+ events annually and serves major entertainment and sports organizations. It supports multiple payment methods including RFID, online and offline ordering, mobile checkout, and real-time sales monitoring. The product operates across merchandise, food & beverage, and concierge services. The company was founded in 2012 and is headquartered in San Clemente, California with 51–200 employees.
atVenu's core stack is Ruby on Rails + React (web) + React Native (mobile), backed by PostgreSQL and Redis, deployed on AWS. Payment processing uses Stripe; backend jobs run via Sidekiq. Analytics tools include Tableau and SAS; compliance uses OneTrust.
Active projects span mobile ordering, payment peripheral integration, reporting enhancements, promotional features for events, and a privacy compliance program including cookie consent implementation and data protection assessments.
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atVenu'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.