LLMO / answer-engine visibilityLLMOSEOAI search
LLMO consultant for agent-ready visibility
Search and answer-engine readiness for people, products and portfolios: structured pages, machine-readable indexes, FAQ schema and citation-friendly content.
Best fit
- Experts, founders and technical teams whose work exists online but is hard for AI systems to summarize accurately.
- Sites that have good projects or products but weak canonical pages and thin machine-readable structure.
- Portfolios and product catalogs that need clearer entry points for clients, recruiters or partners.
Typical output
- Audit of current crawlable pages, titles, descriptions, structured data and internal links.
- Canonical page plan for core offers, products, proof points and FAQs.
- Implementation of JSON-LD, llms.txt, content-index.json and citation-friendly page copy where appropriate.
Evidence
- ABVX exposes public llms.txt, content-index.json, sitemap, schema and structured portfolio pages.
- The About, Work, Books and service pages are designed as human-readable and machine-readable surfaces.
- The site now has focused entry points for high-intent search and LLM retrieval.
Related public evidence
FAQ
Common fit questions.
Is LLMO different from SEO?
It overlaps with SEO, but the emphasis is on being accurately understood and cited by answer engines and AI agents: clear entities, canonical pages, structured data, FAQs, internal links and machine-readable indexes.
Can this help a very low-traffic site?
Yes, but it is a foundation, not a traffic switch. It makes the site easier to understand and cite; distribution, external links and useful public material are still needed for growth.
Start with a short brief
Send what you are building, who needs to understand it, and what decision or launch moment is blocked.