Product
Content Strategy
Content that ranks on Google fails in ChatGPT. We help you optimize for LLM retrieval using insights from Google DeepMind research on information ranking.
Book a DemoWhy Traditional SEO Fails
Content optimized for Google rankings often performs poorly with LLMs because:
Format Mismatch
Long-form keyword-optimized content is hard for LLMs to parse. They prefer structured, comparative data.
Gated Information
Critical details behind forms or login walls are invisible to AI platforms.
Marketing Language
LLMs downrank vague marketing claims. They favor factual, verifiable information.
Our Optimization Framework
LLM-Optimized Structure
Format content for maximum retrievability by AI models based on DeepMind research
Gap Analysis
Identify missing information that prevents ChatGPT from recommending you
Credibility Building
Strengthen trust signals that influence LLM ranking decisions
Implementation Roadmap
Prioritized action plan with specific content updates to maximize impact
The Gemini Optimization Principles
From our founder's work improving Gemini at Google DeepMind, we've identified three core principles that drive LLM content optimization
Verifiability
Every claim must be checkable against other sources, timestamped, specific, and attributed when appropriate
Comprehensiveness
Content must address the main question, obvious follow-ups, edge cases, and alternatives with trade-offs
Accessibility
Information must be publicly available, machine-parseable, regularly maintained, and properly marked up
Typical Results
Improvement in ChatGPT recommendation rates
To see measurable impact
Increase in conversion rates
Ready to win the hidden
LLM sales channel?
Get a full evaluation of how models sell you, plus the fixes to rank, convince, and convert in-chat.
Get my LLM sales audit