Making Brands Visible to AI and LLMs

AI Visibility is a strategic project focused on making brands discoverable by large language models and AI-powered search engines. As users increasingly rely on ChatGPT, Perplexity, and AI Overviews to find answers, being cited by these systems is the new frontier of digital presence.

Project type / Focus

AI Visibility & LLM GEO Strategy

Project duration

1 year

Deliverables

Logo, visual identity, brand guidelines and animation files

Tools used

Figma, Adobe Suite, Framer, Webflow, Claude Code, Mailchimp, Hubspot

Project Link

Amprenta

Company type/ Location

IT Company/ UK

The Challenge

Most brands remain invisible in AI search. When users ask ChatGPT, Perplexity, or Google’s AI Overview for recommendations, only a small percentage of businesses are cited. Large language models prioritize entity recognition, authoritative content, and structured knowledge to determine which brands appear in responses.

Clients reported new leads that attributed their discovery directly to AI recommendations, demonstrating that LLM GEO drives measurable pipeline growth. The work established a repeatable playbook that is now used across our client base to help brands compete and grow in an AI first search landscape.

We began with a full AI Visibility audit — mapping how the brand appeared across ChatGPT, Perplexity, Google AI Overview, and Gemini. From there we built a structured content and entity strategy: defining the brand's knowledge graph presence, structuring authoritative content to match LLM query patterns, and building citation signals across trusted sources.

Scope of Work

LLM GEO (Generative Engine Optimization) is the practice of structuring content, authority signals, and entity data so large language models surface your brand as a trusted answer. Unlike SEO, it focuses on training-data quality, entity prominence, and answer-format content rather than keyword density or backlink volume.

Measurable Results

AI Visibility work creates compounding returns. Brands that get cited by LLMs early gain a structural advantage — their content gets referenced in future training cycles, their entity authority grows, and they become the default answer for their category across every major AI platform.