Which AI engines provide citation data?

Perplexity, AI Overviews, and Copilot provide explicit source citations in their responses. For engines like ChatGPT and Claude that do not cite sources directly, the platform uses content-matching heuristics to infer likely source relationships. Inferred edges are visually distinguished from confirmed citations so you can assess confidence at a glance.

Can I export the citation network data?

Yes. The graph data can be exported as a CSV edge list, a JSON graph format, or a visual PDF snapshot. The API also provides programmatic access to the full graph structure for integration with custom analysis tools.

How far back does the citation history go?

Citation data is stored from the moment you start monitoring. The platform does not have historical citation data from before your account was created. Most users accumulate enough data for meaningful network analysis within four to six weeks of active monitoring.

Feature

diagnosis

Citation Network Graph

Visualise how AI engines connect brands, sources, and recommendations to trace the paths that drive citations.

Quick answer

AI engines do not recommend brands in isolation. They weave a network of citations that connects brands to sources, sources to other sources, and recommendations to the authority signals that justify them. Citation Network Graph maps this network visually, showing you the web of relationships that determines whether your brand gets cited.

How it works

Citation Network Graph in detail

The platform collects citation URLs from engines that provide them (Perplexity, AI Overviews, Copilot) and infers source relationships for engines that do not by analysing response content against known web pages. These citations are stored as edges in a graph database where nodes represent brands, web pages, and domains.

The graph is rendered as an interactive network visualisation. Nodes are sized by citation frequency and coloured by type (your brand, competitor brands, authoritative sources, unknown sources). Edges show the direction and strength of citation relationships. You can zoom into a specific competitor to see their citation sources, or zoom into a specific source domain to see which brands it supports.

Filters let you isolate the graph by engine, by time period, and by query family. A time-lapse view shows how the citation network evolves across monitoring cycles, revealing emerging sources and fading ones. Each node and edge links back to the underlying mention data, so you can drill from a graph insight to the specific AI response that produced it.

Benefits

Why Citation Network Graph matters

Visualise the citation relationships that drive AI engine recommendations

Identify the authoritative sources that feed competitor citations

Discover high-value link-building and content distribution targets

Track how the citation network evolves over time with time-lapse views

Drill from graph nodes to specific AI responses for full context

Use cases

When to use Citation Network Graph

A digital PR team identifies the three review sites most frequently cited by AI engines in their category and targets them for coverage.

An SEO strategist discovers that a competitor's AI visibility spike traces to a single well-cited industry report.

A content director maps the citation paths for their top five prompts to understand which existing pages contribute most.

FAQ

Citation Network Graph FAQ

Related features

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Track up to 25 competitors across every AI engine and see exactly where they outrank you.

Content Optimization Scoring

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Score every page on five dimensions of citation readiness and know exactly what to fix.

Prompt Discovery

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Find the prompts and queries where your brand should appear but doesn't — and prioritise the ones that matter most.

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Get started

Start with the pages and proof that AI can actually use

Run the free audit to see what blocks AI from citing your site. Use the trial when you need ongoing monitoring, attribution, prompt discovery, and team workflows after the first fixes are live.

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