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Before diving into the platform, it helps to understand the key concepts that Superlines is built around.

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Account hierarchy

Superlines uses a hierarchical structure:
  • Organization — your top-level account. It holds your subscription, team members, API keys, and LLM engine configuration.
  • Brand (Domain) — a business entity you want to monitor. Each brand has its own name, website, target market, competitors, prompts, and analytics.
  • Prompts — the questions people ask AI. Superlines tracks how each prompt performs across AI engines.
  • Labels — tags for organizing prompts by topic, campaign, priority, or any custom category.

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What are prompts?

A prompt is a question or query that people type into AI assistants. Examples:
  • “What are the best project management tools for remote teams?”
  • “How do I improve my website’s AI search visibility?”
  • “Which CRM is best for small businesses?”
Superlines tracks these prompts by testing them across multiple AI engines (ChatGPT, Copilot, etc.) and recording:
  • Whether your brand is mentioned in the response
  • Whether your website is cited as a source
  • Which competitors appear
  • The overall sentiment

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What are responses?

A response is an AI engine’s answer to a tracked prompt. Each time Superlines tests a prompt, it captures the full response and analyzes it for:
  • Brand mentions — does the response name your brand?
  • Brand position — in what order is your brand mentioned relative to others?
  • Website citations — does the response link to or reference your domain?
  • Competitor mentions — which other brands appear?
  • Sentiment — is the mention positive, neutral, or negative?

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What are citations?

A citation is a reference to a specific URL in an AI response. When an AI model links to your website (or a competitor’s), that’s a citation. Citations are a strong signal of content authority.
Not all AI engines provide citations. Models with web access (like Perplexity, Copilot, Google AI Overviews, Google AI Mode) cite sources more often than offline models.

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What are fan-out queries?

When an AI model with web access answers a question, it often performs web searches behind the scenes. These internal searches are called fan-out queries. Superlines tracks these to show you:
  • What search terms the AI uses when answering about your topic
  • Where your domain ranks for those searches
  • Opportunities to improve your content for AI retrieval

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How the analysis works

1

Prompts are tracked

You add prompts to track for each brand — or let Superlines auto-discover them.
2

Automated testing

Prompts are sent to all your enabled AI engines daily.
3

Responses are collected

Full responses are captured and stored.
4

Brand detection

Responses are scanned for mentions using your brand name and variations.
5

Citation extraction

All URLs referenced in responses are parsed and tracked.
6

Metrics are calculated

Brand Visibility, Citation Rate, Share of Voice, Average Position, and more.
7

Insights are generated

Trends, alerts, and recommendations are surfaced.