B2B flight content and virtual interlining API for airlines and OTAs
Tripstack sells virtual interlining and flight content via API, stitching together itineraries across carriers that don't partner directly. Its stack pairs a .NET Core/C# service layer with a heavy streaming and analytics tier (Redpanda, Spark, Druid, Airflow) across GCP, AWS, Azure and OpenStack. Kubernetes shows up as both in use and being replaced, while job posts describe moving the data stack onto it, so the container platform is clearly in flux.
Tripstack is a Toronto-based provider of flights as a service, founded in 2016 and part of Etraveli Group since 2019. It gives airlines, online travel agencies and other distribution partners API access to global flight content and virtual interlining, which combines low-cost, full-service and non-partner carriers into single itineraries. Partners can also use related services such as payments, fraud prevention, pricing and customer support. The company has 51–200 employees, offices in Canada, India and Poland, and processes very high daily search volumes.
Tripstack runs C# and .NET Core services on Kubernetes and Docker across GCP, AWS, Azure and OpenStack. It uses Terraform, Helm and ArgoCD for infrastructure, and Redpanda, Spark, Druid, Airflow and PostgreSQL for data.
Job posts point to a flight combination engine, flight content integration, a data stack migration to Kubernetes, A/B testing for the virtual interlining product, internal platform tooling and AI-assisted development infrastructure.
Tripstack is hiring in Canada, China and Malaysia, and hiring is accelerating. Open roles are mostly in engineering, support and product, at mid and senior levels.
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tripstack'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.