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Traffic Quality

Separate people from machines

Suspicious traffic, reported as a measurement problem.

Requests that failed a challenge, arrived from networks with poor reputation or probed for paths that do not exist are held apart from human traffic and shown with the context that made them suspicious. The question answered here is not whether you are under attack. It is how much of last week was real.

Security Traffic

  • Challenge issued, passed and abandoned
  • Network reputation and ASN context
  • Suspicious volume by path and region
  • Challenge waves beside human trends

How it helps

What Security Traffic gives you

1

The outcome, not just the trigger

A challenge that is solved and a challenge that is abandoned mean different things. Classification uses what happened after the challenge, which keeps a cautious rule from writing off traffic that turned out to be people.

2

Network context, not single requests

Autonomous system, address range history and prior behaviour turn one odd request into a pattern worth naming. Thirty thousand requests from a single network inside an hour is a different finding from thirty thousand spread across a continent.

3

Where the friction landed

Challenges are reported by path, country and device, next to human visits for the same slice. If human traffic falls in one country while challenges there rise, that correlation is the first thing to check before the drop is read as demand.

Connect a site today. Read tomorrow's brief instead of building it.

Connect a site and the first brief arrives with the day's changes already explained — traffic separated from bots, conversions attached to revenue, and the evidence behind every sentence one click away.

Real people separated from bots Every answer shows its evidence Reveliqo runs on Reveliqo