Case Study: Royal FloraHolland achieves data-driven transformation and improved logistics with Amazon Web Services (AWS)

Xebia Uses Machine Learning on AWS to Evolve Royal FloraHolland's Practices

Royal FloraHolland, the world’s largest flower auction cooperative with a century-long legacy and 145,000 daily transactions, set out to digitize and become more data-driven so growers and buyers could trade beyond the physical auction. The company faced operational challenges—most notably unreliable trolley arrival forecasts that disrupted staffing and logistics—as well as inconsistent product images and limited online buyer recommendations, all of which constrained revenue and customer experience.

To tackle this, Royal FloraHolland partnered with Xebia and migrated its "digital greenhouse" to AWS, building a containerized, microservices platform with automated pipelines and ML tooling (Amazon Kinesis, S3, Glue, SageMaker, Airflow, API Gateway). Deep learning models for trolley logistics, image-quality recognition, and a recommendation engine improved operational planning and labor costs, raised seller conversion through better photos, and surfaced real-time alternatives for buyers—accelerating the cooperative’s shift to data-driven decision making and ongoing digital transformation.

Royal FloraHolland

Remco Wilting

Head of Data and Data Science