Real results from
real fraud problems

How these case studies work

Each scenario is a composite built from real attack patterns that Sentinel detects across its customer base. The fraud techniques, detection signals, and outcome metrics reflect what actually happens in production environments. Company names, team sizes, and specific revenue figures are representative rather than literal — they are designed to accurately reflect the scale and type of fraud each vertical faces.

Sentinel's detection covers three layers: network intelligence (VPNs, residential proxies, datacenter IPs, Tor exit nodes), device intelligence (headless browsers, antidetect browser spoofing, emulators), and behavioral signals (velocity, device clustering, session anomalies). The case studies below show how those layers interact to stop fraud that IP-only tools miss entirely.

Named customer references with attribution are available under NDA for enterprise prospects. Contact us to request a reference call with a customer in your vertical.

Illustrative scenarios. The case studies below are representative composites built from attack patterns Sentinel detects in production. They do not name a single specific customer. Real named customer references with attribution are available under NDA on request — contact us.