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Before diving into MentionLab, it helps to understand how the platform is structured. This page covers the core concepts you’ll encounter throughout the product.

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Organization

An organization is the top-level entity in MentionLab. It represents your company or team and contains all your projects, users, and billing information.
  • Every user belongs to at least one organization.
  • After signing up, you either create a new organization or join an existing one via invitation.
  • Organization-level settings include user management, billing, and API keys.
You can switch between organizations at any time using the organization selector in the top navigation bar.

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Project

A project represents a brand, product or anything you want to monitor across AI platforms. Each project contains its own set of queries, competitors, tags, and analysis results. When you create a project, you configure:
One organization can have multiple projects — for example, one per product line or brand.

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Queries

A query is a question or prompt sent to AI platforms to observe how they respond and whether they mention your brand. For example:
  • “What is the best project management tool?”
  • “Which CRM software do you recommend for small businesses?”
Queries are the foundation of your monitoring. The more relevant queries you configure, the broader your coverage of how AI platforms perceive your brand.
Queries can run in multiple languages. If you have 10 queries running in 3 languages, you have 10 unique queries but 30 total queries.

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Tags

Tags are labels you assign to queries to organize them into groups. They help you segment and analyze your results by topic, intent, product feature, or any custom category. For example, you might create tags like:
  • Pricing — for queries about cost comparisons
  • Features — for queries about product capabilities
  • Industry — for queries about sector-specific tools
MentionLab also supports Response Tags, which are tags applied to individual AI responses (not queries). These let you categorize results after they’ve been collected.

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Entities, Brands & Competitors

Every brand named in an AI response becomes an entity in your project, automatically. Entities carry four flags that decide what they mean to you:
  • Primary — your main brand, the one every “your brand” metric refers to
  • Owned — other brands you own
  • Competitor — brands you’re tracking against
  • Blacklisted — false matches, excluded from analysis entirely
Detection is automatic, but the Competitor flag is not — you set it yourself, during project creation or later from Project settings → Entities.
For each entity you can also configure:
  • Aliases — alternative names or spellings, so all variants land on one entity
  • Domains — the sites the entity owns, used to attribute cited sources
  • Group / Division — a two-level structure for organising many entities
See Competitors & Brands for the full walkthrough.

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AI Models (Platforms)

MentionLab queries multiple AI platforms to give you a comprehensive view of your brand’s presence. Supported platforms include:
  • OpenAI — ChatGPT, GPT 5.3-chat
  • Anthropic — Claude Haiku 4.5
  • Google — Gemini, Gemini 2.5 Flash, Gemini 3 Flash Preview, AI Overview, AI Mode
  • Perplexity — Sonar
  • DeepSeek — v3.2
  • And more as they become available
Models fall into two categories in the picker: Scraping models read the real consumer product (what a person actually sees), while API models query the provider’s API directly.
Shopping assistants — Amazon Rufus and Alexa — are also available, along with other specialised surfaces. They are add-ons rather than part of the standard model set, so they only appear in your model picker once enabled. Talk to our sales team to add them to your organization.
You choose which platforms to include when setting up your project or when performing a manual analysis. Each platform may surface different sources and mention different brands, so querying multiple platforms gives you broader coverage.
Not all AI models are available in every country. Check the Models Availability page for regional restrictions.

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Results & Analysis

After your queries run, MentionLab analyzes each AI response to extract:
  • Mentions — Which brands were named, how many times, and in what position
  • Sources/Citations — Which websites the AI cited when building its response
  • Sentiment — Whether the AI’s mention of your brand was positive, neutral, or negative
  • Fan-outs — Follow-up questions the AI suggested as related topics
  • Shopping products — Product recommendations found in shopping-related responses
  • YouTube citations — Videos and channels cited alongside web sources
Results are displayed across multiple analysis pages, each focusing on a different dimension of your data.

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Tokens

MentionLab bills in tokens. Each query execution consumes tokens from your organization’s balance: Tokens per run=Queries×AI Models×Iterations\text{Tokens per run} = \text{Queries} \times \text{AI Models} \times \text{Iterations} The recurrence frequency then decides how often you pay that. You can view your balance, daily usage and full activity ledger in the Billing section of your organization settings.
The REST API still calls this unit credits. Tokens and credits are the same thing.

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Key relationships

Here’s how the main concepts fit together:Organization → has many Projects → each has Queries (grouped by Tags) → which generate Results with Mentions, Sources, and Sentiment data → compared against Competitors.