Case Study: Flow Networks achieves real-time, personalized payments at scale with Confluent

Flow Disrupts Payment Processing Industry with Confluent at Its Core

Flow Networks, a San Francisco–based payments startup, needed a real-time B2B2C payments platform to contextualize streaming payment data and deliver highly personalized customer experiences. To meet requirements for scalability, resilience, and low latency, Flow chose Confluent Cloud on AWS as the event-driven foundation for its platform.

Confluent implemented a Kafka-based event-driven microservices and streaming ETL backbone that decouples services and integrates MongoDB, AWS S3, and Databricks (using Kafka Connect, Debezium, and ksqlDB for real-time processing). With Confluent, Flow runs pipelines at roughly 1,000 transactions per second, achieves end-to-end processing in about one second per engagement, maintains full data protection via RBAC and audit logs, and has a future-proof foundation for new real-time features.

Flow Networks

Klas Hesselman

Co-Founder