Analyze and improve your reputation in AI
Discover how artificial intelligence perceives, mentions, and recommends your brand.
AIBrandpulse360 is a structured methodology for analyzing brand reputation within artificial intelligence systems and large language models (LLMs).
Through our analytics platform, we measure how tools such as ChatGPT, Gemini, Perplexity, or AI Overview interpret your brand, which sources they rely on, and how they influence the recommendations users receive.
Turn your AI reputation into a competitive advantage
More and more users are consulting artificial intelligence tools before making decisions.
When a user asks ChatGPT or another AI system for recommendations within a category, your brand’s digital reputation in AI determines whether you appear in the response or not.
The AIBrandpulse360 methodology makes it possible to analyze:
- Whether AI recommends your brand over your competitors
- What information it uses to describe your company
- Which sources influence the perception of your brand
- Your company’s positioning in AI-generated responses
Our platform allows you to continuously monitor this data to understand how your AI reputation evolves over time.
What the AIBrandpulse360 methodology analyzes
Monitor your online reputation across the main AI platforms
Analyze when and why ChatGPT mentions or recommends your brand.
Evaluate how Google Gemini interprets your brand within its knowledge.
Detect when your brand appears cited as a source or recommendation.
Analyze how DeepSeek interprets and recommends brands, identifying its reasoning logic and the factors that influence visibility.
AIBrandpulse360
: Methodology for measuring
digital reputation in AI
AIBrandpulse360 is not just a monitoring tool. It is a methodology designed to analyze a brand’s presence, perception, and positioning within artificial intelligence systems.
Our methodology analyzes hundreds of relevant queries for each industry in order to understand how a brand appears in AI-generated responses, which companies artificial intelligence recommends when users ask category-related questions, which sources influence a company’s digital reputation, and what opportunities exist to improve its positioning within AI environments.
The AIBrandpulse360 platform enables this methodology to be applied continuously, making it possible to track the evolution of a brand’s reputation in the AI ecosystem and identify strategic opportunities to improve its visibility in responses generated by language models.
Turn AI reputation analysis into an actionable strategy
We base the study on your business objectives
Developed by and for marketing analysts
Local, language, and LLM segmentation
We provide you with an action plan tailored to your strategy
Clients who already trust us
Request an analysis of your AI reputation
Discover how artificial intelligence models interpret your brand and how you can improve your positioning in AI-generated responses.
Analyze how your company appears on artificial intelligence platforms such as ChatGPT, Gemini, AI Overview, Perplexity, and Google AI, and understand what information these systems use to describe, recommend, or position your brand against your competitors. Through the AIBrandpulse360 methodology and its analytics platform, you can monitor your presence in these environments and understand how your
FAQ
What is AIBrandpulse360?
AIBrandpulse360 is a methodology designed to analyze brand reputation within artificial intelligence systems and large language models (LLMs).
It helps understand how tools such as ChatGPT, Gemini, Perplexity, or AI Overview perceive, mention, and recommend a company within their AI-generated responses.
This methodology is applied through an analytics platform that allows monitoring the evolution of a brand’s presence and perception in artificial intelligence environments.
What is AI reputation?
AI reputation refers to how artificial intelligence systems interpret, describe, and recommend a brand when users make queries.
Unlike traditional digital reputation, AI reputation depends on how language models process information available on the internet and which sources they use to construct their responses.
How does AIBrandpulse360 analyze brand reputation in AI?
The AIBrandpulse360 methodology analyzes hundreds of queries related to a specific industry to understand how artificial intelligence models respond.
Based on these queries, it evaluates indicators such as brand presence, ranking against competitors, the perception conveyed by AI, semantic authority, and the sources used by AI systems to generate responses.
Can a company improve its AI reputation?
Yes. Understanding how language models interpret a brand makes it possible to identify opportunities to improve its presence in AI-generated responses.
Through the analysis provided by the AIBrandpulse360 methodology, it is possible to detect which sources influence AI systems and which strategies can help improve a company’s positioning within these systems.
What is the difference between digital reputation and AI reputation?
Traditional digital reputation is based on elements such as reviews, media presence, or SEO positioning.
AI reputation depends on how artificial intelligence models interpret all that information to generate responses. This means a brand can have a strong online reputation but still not appear in AI-generated recommendations if the models do not consider it relevant within their knowledge.
What platforms does AIBrandpulse360 use to analyze AI reputation?
The AIBrandpulse360 methodology analyzes brand presence across the main artificial intelligence platforms used by users, including ChatGPT, Gemini, Perplexity, AI Overview, and other environments powered by language models.
What metrics does AIBrandpulse360 analyze?
AIBrandpulse360 analyzes indicators such as brand presence in AI-generated responses, positioning against competitors, the perception that artificial intelligence conveys about the company, the brand’s semantic authority within its industry, and the sources used by language models to generate their responses.
How do sources influence AI reputation?
Language models use different sources of information to construct their responses.
These sources may include digital media, corporate websites, specialized articles, or knowledge bases.
Analyzing which sources influence AI makes it possible to understand what information is shaping a brand’s reputation within these systems.