Case Study: TrafficGuard achieves real-time, scalable ad-fraud protection with Imply

TrafficGuard - Customer Case Study

TrafficGuard, a fraud-prevention provider for large digital advertisers and agencies, needed reliable real-time reporting to protect ad spend and optimise campaigns. Their legacy Redshift/Aurora + ETL batch architecture couldn't keep up as volume and dimensionality grew—TrafficGuard needed to process thousands of queries per second across billions of daily transactions with dozens of dimensions and measures and surface insights with minimal latency. They evaluated options and chose Druid, partnering with Imply to operationalise it.

Working with Imply (using Imply Cloud and Imply’s Pivot UI), TrafficGuard connected Druid to AWS Kinesis for end-to-end streaming analytics, removed infrastructure overhead, and sped time-to-market for product innovations. The new stack supports datasets up to 95 dimensions and 63 measures, ingests data in real time, noticeably reduced stored data via Druid compression, delivers interactive, snappy visualisations, and enabled TrafficGuard to meet high concurrency and low-latency requirements while focusing engineering effort on fraud detection rather than ops.

TrafficGuard

Raigon Jolly

Head of Data Science and Analytics