Comtravo - Empowering Purposeful Business Travel
We are a tech-savvy team of travel professionals and customer service heroes with the common goal of simplifying business travel with an AI-based approach. We've been revolutionizing the business travel market for 6 years and are growing fast with now more than 250 colleagues, backed by top investors like Microsoft, Project A and Creandum.
At Comtravo, we always see challenges as opportunities and thus we see the biggest challenge for the travel industry, the spread of the COVID-19 virus and the limitations it brings, as the biggest opportunity for us. We have successfully adapted our strategy and this has resulted in the strongest growth so far in our successful company history.
Being both - an extremely customer service oriented and a top tech company - our services evolve around two major applications that we develop for the internal and the external management of business trips - for our agents and for our customers, respectively. Both applications interact with our in-house booking engine and many APIs to our suppliers.
Our tech stack:
Our frontends are built in angular / typescript. Our offer and booking management backends are primarily built in node.js
/ typescript and consists of around 20 major RESTful services plus around 60 micro services.
We are using state-of-the-art technologies, such as natural language processing and machine learning techniques, to automate our booking and fulfilment pipelines and leverage past data to improve our customers experience. These are primarily developed in python.
We carefully design our systems to collect the right data at the right places and make such data available in a compliant way to enable a data driven mind set throughout the company.
We make heavy use of docker and terraform and are running on AWS. Services are coupled by events and run on ECS and lambda.
We invest in shared components, libraries, automated tests, monitoring and sane interfaces. Together with a strong CI/CD pipeline we are able to release many times per day to production.