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

​
Account hierarchy

Superlines uses a hierarchical structure: 
Organization
├── Brand (Domain) 1
│   ├── Prompts + Labels
│   ├── Competitors
│   └── Analytics
├── Brand (Domain) 2
│   ├── Prompts + Labels
│   ├── Competitors
│   └── Analytics
└── Team Members (org-wide)
  • 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.

​
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

​
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?
  • 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?

​
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) cite sources more often than offline models.

​
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

​
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, and more.
7

Insights are generated

Trends, alerts, and recommendations are surfaced.