LLM Optimization: influence how AI assistants talk about you.
We audit what models currently say, identify the sources shaping those answers, and build the corroborated presence that changes them.
Typical outcomes
LLM Optimization
- Models audited
- ChatGPT, Gemini, Claude, Perplexity
- Fact accuracy
- Tracked
- Recommendation share
- Monitored
Ranges reflect typical programme targets and depend on starting point, competition and implementation speed.
Symptoms that usually bring teams to us
If any of these feel familiar, the underlying cause is almost always measurable and fixable.
AI assistants recommending competitors
Outdated or incorrect facts about your brand
No presence in the sources models rely on
Product and pricing details misrepresented
How we deliver llm optimization
Model response audit
Systematic prompting across models to capture how you are represented.
Source influence mapping
Identify the third-party sources shaping model answers.
Presence building
Accurate, consistent brand facts published where models retrieve.
Deliverables, not decks
Everything is delivered inside the Rankora platform alongside the data that justifies it, so your team can act immediately.
- LLM representation audit
- Source influence map
- Fact consistency programme
- Brand entity optimisation
- Ongoing monitoring
Sectors where we apply this most
LLM Optimization questions
AI Search
AI SEO
Optimise for visibility across Google AI Overviews, ChatGPT, Gemini, Claude, Perplexity and every emerging AI search experience.
AI Search
GEO
A structured discipline for earning citations in generative answers — from Google AI Overviews and AI Mode to Perplexity.
Content & Authority
Digital PR
Newsworthy campaigns that earn coverage, links and brand mentions from publications your audience trusts.
Ready to talk about llm optimization?
Tell us about your site and goals. We will come back with an honest view of the opportunity and a sequenced plan.