Adityagen.ai built detection infrastructure that empowered 200+ fraud analysts to identify millions of abusive accounts — converting individual review into coordinated, ring-level intelligence.
The ad exchange ecosystem faced coordinated abuse at massive scale — fraud networks operating across millions of accounts with behavioral patterns that individual account review could never catch. Manual review processes were reactive and slow, unable to surface the ring-and-chain relationships that distinguished coordinated fraud from isolated violations.
The detection challenge was compounded by the scale of data involved: processing massive volumes of account behavioral data in near-real time while maintaining accuracy high enough to avoid penalizing legitimate advertisers. Continuously evolving fraud patterns required the system to be architecturally adaptable, not just accurate at point-in-time.
"The goal wasn't to catch more fraud — it was to give 200 human reviewers the intelligence to catch fraud that no single person could ever see alone."
