> For the complete documentation index, see [llms.txt](https://docs.aloop.icustomer.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aloop.icustomer.ai/ireveal/ai-referral-measurement.md).

# AI-referral measurement

AI-referral measurement in iReveal: agents and LLM referrals as a first-class, identified, measurable channel.

AI agents acting on your behalf, and on your visitors' behalf, are invisible to session analytics. A browsing agent does not accept a cookie banner the way a person does, does not stitch into a session model built for humans, and does not show up in a channel report that only knows paid, organic, and direct. Traffic from AI assistants and LLM answers is already arriving; most measurement stacks cannot see it, let alone credit it.

## Agents are first-class actors

iReveal treats humans **and agents** as first-class, identified actors. An agent's visit resolves to an immutable ID the same way a person's does, its actions are captured server-side at full fidelity, and what came of them lands in the same trace, from event to identity to outcome.

## LLM referrals as a channel

That makes AI referral a channel you can measure rather than a mystery slice of direct traffic: see the visits AI referrals drive, follow them to resolved people and accounts, and read what those referrals produced in pipeline and revenue, on the same [outcome tracking](/ireveal/outcome-tracking.md) every other channel gets.


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