Case Study: TrafficGuard achieves real-time ad fraud prevention and cost-efficient scaling with Qubole

TrafficGuard Halts Digital Ad Fraud With Qubole

TrafficGuard, a SaaS product from Adveritas, detects and prevents digital ad fraud by using machine learning to block invalid impressions, clicks, and installs in near real time. Facing fraud that increasingly mimics human behavior, the company needed a scalable, cost‑efficient big‑data infrastructure to process rapidly growing, volatile traffic and to detect evolving threats without relying on slow, end‑of‑period reconciliation.

By partnering with Qubole, TrafficGuard built a cloud‑native pipeline (Spark, TensorFlow, Presto, etc.) with workload‑aware autoscaling and intelligent AWS Spot management, enabling fast spin‑up of clusters and aggressive downscaling to cut costs. The solution now processes roughly 1 billion transactions (~10 TB) per day, supported rapid 12× data growth, sped time to market, reduced operational overhead, and powers more than 10 ML models that improve fraud detection and lower false positives.

TrafficGuard

Pravin Todkar

Senior Engineer, AI, Data, and Cloud Services