Bot traffic management, agentic-traffic classification, and fraud mitigation at the edge -- built for a web where most requests are no longer from a browser.
Traffic classification
Benign search spiders
0% of edge traffic
Allow-listed by verified reverse-DNS.
LLM / AI scrapers
0% of edge traffic
Rate-limited, served a lightweight response.
Benign automation
0% of edge traffic
Passed through with header-based identification.
Credential-stuffing bots
0% of edge traffic
Blocked at the edge before origin.
Scalping / fraud bots
0% of edge traffic
Challenged, then blocked on repeat offense.
0.0ms
Median latency added by edge classification rules
0.0%
False-positive rate on verified crawlers
0%
Coverage against known credential-stuffing signatures
LLM-driven agents now browse, fill forms, and check out on behalf of users -- traffic that looks automated but isn't malicious. Classification rules built for "bot vs human" are being rebuilt around intent instead: is this request acting on a real person's behalf, or extracting value at scale.
Let's talk through your classification rules.