Case Study: TripActions achieves real-time analytics scale and 80% lower TCO with Provectus

TripActions enables real-time data analytics and machine learning to accelerate business growth

TripActions, a corporate travel management company, needed a more scalable analytics foundation as its historical and operational data grew too large for its existing infrastructure. Its Amazon Elasticsearch-based setup, along with scattered data across Redshift, MySQL, and S3, created data silos, delayed analytics, and increased total cost of ownership. Provectus helped TripActions address these challenges with a new streaming data platform.

Provectus delivered a real-time data solution built on Apache Kafka, with data ingestion, processing, enrichment, and transformation pipelines feeding Amazon S3, AWS Glue, and Amazon Athena for sub-second queries. The migration consolidated historical data from ElasticSearch, Redshift, and RDS into a unified data lake and separated data team services into a dedicated Data VPC. As a result, TripActions cut TCO by 80%, shortened release cycles for data analytics projects by 12x, increased monthly business growth by more than 30%, and powered over 200 data products.

TripActions