Case Study: HUMAN achieves 10X faster bot detection and investigations with Imply

HUMAN expedites bot detections and investigations by 10X

HUMAN, a cybersecurity company that protects applications and digital media from bot attacks, needed a scalable, low-latency way to analyze trillions of events from its Human Verification Engine (HVE). HVE makes more than 10 trillion decisions per week and must classify traffic in under 12 milliseconds; analysts previously relied on complex Snowflake queries or Jupyter notebooks, which were slow and hard to use. HUMAN engaged Imply (using Imply Pivot) to provide a visualization and database layer that could handle massive-scale ingestion and ad-hoc analysis without heavy SQL expertise.

Imply delivered Imply Pivot and a Snowflake-to-Imply ingest pipeline so ~50 users can perform drag-and-drop visual analysis on three months of data with sub-second responses. As a result, Imply helps HUMAN analysts discover new and undetected bots about 10X faster, investigate 10–15 new leads per week, feed findings back into HVE for automated detection, and improve reporting and customer response times.

HUMAN

Marion Habiby

Senior Data Ops