Live event ticketing platform with data-driven yield optimization
Victory Live operates a ticketing platform for sports, concerts, and theater rightsholders, resellers, and affiliates. The tech stack reveals heavy investment in data infrastructure—dbt, Snowflake, Dagster, Azure Data Factory, and Airflow—paired with active AI work (LLM embeddings, agentic workflows, semantic data models), suggesting a shift from static pricing automation toward predictive revenue optimization. Current hiring spans engineering, sales, data, and product with accelerating velocity, while internal pain points center on partner adoption, data freshness, and moving from reactive to proactive insights—a roadmap that aligns with the AI projects underway.
Victory Live provides ticketing distribution, yield management, and automation for live event rightsholders. The platform connects multiple sales channels—direct, resellers, and affiliates—and uses data-driven pricing and inventory optimization to maximize revenue. The company serves mid-market and enterprise event organizers across sports, concerts, and theater. Operations are based in Atlanta with technical infrastructure on AWS and Azure. The product emphasizes real-time reporting, partner onboarding, and API integrations to enable programmatic ticket sales.
Core data: Snowflake, dbt, Dagster, Azure Data Factory, Fivetran, Apache Airflow. Cloud: AWS, Azure with Kubernetes (EKS, AKS). CRM/ops: HubSpot, Salesforce, Jira, Okta. Monitoring: Datadog, Elasticsearch, Grafana. Infrastructure-as-code: Terraform, Bicep, CloudFormation.
Open distribution adoption, partner onboarding, API integration, AI-powered feature pipelines (LLM retrieval, embeddings, agent workflows), semantic data models for analysts, and robust ELT pipelines using dbt, Snowflake, and Dagster.
Victory Live'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.