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AI Traffic shows what AI systems and their users do with your site. It leads with evidence of what AI systems crawl, retrieve, and cite, then shows the visible referral and conversion tail from platforms like ChatGPT, Claude, Perplexity, and Gemini. Open it from Insights › AI Traffic in the project sidebar. It has four tabs:
  • Overview - AI traffic signals from training crawls and citations through answer fetches to referral sessions and conversions, then your top pages
  • Crawls & fetches - training-crawler and answer-fetcher activity by platform, with recent answer fetches
  • Referrals - referral sessions, conversion events and direct traffic, broken down by AI engine and landing page
  • 404 Demand - missing pages AI systems keep requesting
To compare Google search clicks with AI citations and review page-level opportunities, open Insights › Audit and select the Pages tab.

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What AI Traffic Tracks

AI Traffic answers two questions:
  1. What are AI systems retrieving and citing? - Detects crawlers and answer fetchers such as GPTBot, ClaudeBot, and PerplexityBot, alongside citation evidence from Visibility.
  2. What visible human activity follows? - Tracks attributable referral sessions and conversions without treating them as the full measure of AI-driven demand.
AI referrals are systematically undercounted because most AI-driven visitors arrive as direct traffic. Referral and conversion metrics are the visible tail of AI traffic, not a complete linear funnel. AI Traffic is fed by sensors you connect once: the tracking snippet for referral sessions, Cloudflare or edge middleware for crawler and answer-fetcher requests, GA4 or PostHog for conversions, and Search Console for classic-search comparison. DevTune classifies each request server-side and presents the data with trends, platform breakdowns, and top pages.

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Why AI Traffic Matters

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AI Platforms Are a Growing Traffic Source

As more users rely on AI assistants to find information and products, the traffic they send to websites is becoming a meaningful channel. Understanding this traffic helps you:
  • Measure retrieval and visibility - See which content AI systems fetch and cite before looking at downstream activity
  • Track AI bot crawling - Know which AI platforms are indexing your content, how frequently, and which pages they visit most
  • Interpret the visible tail - Pair AI Traffic with Visibility while treating attributed referrals and conversions as an undercounted fraction

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Beyond Traditional Analytics

Standard analytics tools like Google Analytics do not break down AI bot traffic or AI referral traffic in useful ways. AI Traffic is purpose-built to:
  • Distinguish AI bots from regular crawlers
  • Identify referral traffic specifically from AI conversation platforms
  • Detect AI-sourced visits via utm_source parameters
  • Show trends and breakdowns by AI platform

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Plan Requirements

AI Traffic is included on every paid plan. The monthly event allowance and how long raw events are retained scale by plan; see Working with Projects for the per-plan figures.

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What Gets Detected

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Bot Crawlers

DevTune detects AI bot crawlers by their user-agent strings:

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AI Referral Traffic

DevTune detects visitors arriving from AI platforms by checking the referrer URL:

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UTM Source Detection

DevTune also checks the utm_source query parameter for AI platform identifiers (e.g., chatgpt, claude, perplexity, gemini, copilot). This catches traffic from AI platforms that include UTM parameters in their outbound links.

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Traffic Classification

Every visit is classified into one of three types:
  • Bot - An AI crawler indexing your content
  • Referral - A human visitor arriving from an AI platform
  • Other - Regular traffic (not AI-sourced)
Classification happens entirely server-side. The tracking snippet sends raw signals (user agent, referrer, page URL) and DevTune handles all detection logic. This means detection rules are updated centrally without requiring snippet changes on your website.

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How It Works

  1. You add a JavaScript snippet to your website (a single <script> tag)
  2. On each page load, the snippet sends a lightweight beacon to DevTune
  3. DevTune classifies the visit by traffic type and AI platform
  4. Data is summarized into hourly and daily views
  5. Insights › AI Traffic displays trends, platform breakdowns, and top pages
The snippet is approximately 3KB, uses navigator.sendBeacon() for minimal performance impact, and generates an anonymous session ID (stored in sessionStorage) to count unique sessions without tracking individual users.

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Privacy

  • The snippet does not use cookies
  • Session IDs are anonymous and stored only in sessionStorage (cleared when the tab closes)
  • The snippet collects no personally identifiable information
  • All data is associated with your project, not with individual visitors
From @devtune/ai-traffic 0.3.0 the edge middleware sensor sends the address a matched crawler request arrived from, so DevTune can check the crawler against the networks its operator publishes. Earlier versions send no address, and their records are stored as unverified. Cloudflare pulls use the same check when its analytics response includes an address. Every request is stored with a verdict: verified, failed, or unknown when the check could not be made. Unknown requests distinguish a sensor that supplied no address, an operator with no published way to check its addresses, and a check that was temporarily unavailable. Older unknown requests appear as before verification because they predate this detail. Only the verdict and reason are kept. An address is sent only for a request whose user agent matches the AI bot registry, so ordinary browser traffic never carries one. That match is on the user agent, and anyone can send a crawler’s user agent, so a person whose client does that would have their address sent. That is the same fact the check exists to handle, and it is why the address is used to reach a verdict and then discarded rather than stored. Set trustedProxy: "none" in the package to send no address at all, in which case that traffic is stored as unverified.

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Getting Started

  1. Choose Your Sensors - Work out which sensors you need
  2. Set Up Sensors - Connect the sensors that feed AI Traffic
  3. Read AI Traffic - Explore your demand data

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Next Steps