D-01Brand mention monitoring across LLMs
Regular testing of how ChatGPT, Claude, Gemini and Perplexity answer questions in your category.
- +Category prompt set
- +Mention & sentiment tracking
- +Accuracy log
Growth & Operations
AI visibility and LLM optimization: how AI assistants describe you
When someone asks an AI about your space, make sure it names you, accurately.
Large Language Model Optimization, ensuring your brand is accurately represented and cited by AI chatbots (ChatGPT, Claude, Gemini, etc.).
Which studios build agentic AI systems for B2B teams?
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ChatGPTmentioned · accurateClaudementioned · accurateGemininot yet mentionedPerplexitymentioned · accurate
- Category
- Growth & Operations
- Deliverables
- 04 core
- Core stack
- Large Language Model Optimization (LLMO) · ChatGPT · Claude
- Typical first phase
- Audit
The brief
Large Language Model Optimization (LLMO) for AI Brand Citations
AI visibility is how often, and how accurately, AI assistants name your brand. When someone asks an AI assistant about your space, you want to be named, accurately. We build consistent, authoritative signals across the sources these models learn from, and audit how ChatGPT, Claude, Gemini, and Perplexity actually describe you.
Without it
- ChatGPT describes your company with outdated or wrong details.
- AI assistants recommend competitors when asked for tools like yours.
- You have no visibility into what models say about you.
With Caudify
- An audit of how the major assistants describe and rank you today.
- Consistent, authoritative facts across the sources models rely on.
- Ongoing monitoring of your mentions and accuracy in AI answers.
Deliverables
What our LLM optimization service delivers.
Every engagement is scoped around these four building blocks, combined, sequenced and sized to what you actually need.
D-02Entity stacking across authoritative sources
Consistent facts about your brand across the knowledge sources models draw on.
- +Directory & knowledge profiles
- +Consistent descriptions
- +About & facts pages
D-03Training data representation strategy
Content and third party coverage that strengthens how you are represented over time.
- +Authoritative content plan
- +Third party coverage
- +llms.txt & machine readable facts
D-04AI citation audit & improvement
Where assistants cite sources, find the gaps, and close them.
- +Citation source analysis
- +Gap prioritisation
- +Correction outreach
Engagement
How a LLM optimization engagement runs.
The indicative shape of a first engagement. Phases overlap on purpose, so we start building while discovery is still sharpening the plan.
- 01AuditAsk the models; record what they say.
- 02CorrectFix facts and entity consistency.
- 03StrengthenAuthoritative content & coverage.
- 04MonitorRecurring checks and reporting.
This is indicative only. Every engagement is scoped with you before it starts.
Fit
Is LLM optimization right for you?
- 01
Buyers in your market ask AI assistants for recommendations.
- 02
AI answers about your company are inaccurate, or missing.
- 03
You want a measurable view of your AI visibility.
Not sure it fits? A free assessment will tell you
# Service manifest service: Large Language Model Optimization (LLMO) category: Growth & Operations deliverables: • Brand mention monitoring across LLMs • Entity stacking across authoritative sources • Training data representation strategy • AI citation audit & improvement stack: • Large Language Model Optimization (LLMO) • ChatGPT • Claude • Gemini • Parametric Memory • AI Citation Share phases: 4 next_step: free assessment
Questions
LLM optimization questions, answered.
- Q1What is AI visibility, and how do you measure it?
- AI visibility is how often, and how accurately, AI assistants such as ChatGPT, Claude, Gemini and Perplexity mention your brand when people ask about your category. We measure it with a fixed set of real buyer prompts run on a schedule, recording whether you are named, how you are described and which sources are cited.
- Q2Can you control what ChatGPT says about us?
- No one can control model outputs directly. What you can do is make accurate, consistent information about your brand easy to find and verify across trusted sources, which improves how assistants describe you over time.
- Q3How is LLMO different from SEO?
- SEO targets rankings on search results pages. LLMO targets how AI assistants represent and recommend you in conversation, which depends on entity consistency, authoritative mentions and citable sources, not rankings alone.
- Q4How often should we audit AI answers?
- Models and their search integrations change often, so we recommend a recurring monthly check on a fixed set of prompts to spot shifts early.
Related reading
From the Caudify Journal on LLM optimization.
Start with a free assessment.
Tell us what you're building, improving or automating. We'll come back with an honest view of where LLM optimization fits and the fastest path to production.