Fetch
AI crawlers, GPTBot, CCBot, Google-Extended and others, request your pages under their own documented bot rules. Your robots.txt posture and server behavior decide whether they get in.
Services / Search
Built for the machines that read the web.
AI crawlers and shopping agents don't browse, they fetch, chunk, and retrieve. Agentic SEO configures your site's machine posture: crawler directives, llms.txt, agent-ready content, and retrieval behavior, so AI systems can find, parse, and cite you.
The machine layer
How AI crawlers read youHow AI systems retrieve.
Classic SEO optimizes for Googlebot's index. Agentic SEO optimizes for a different pipeline, the one answer engines and shopping agents run: fetch, parse, chunk, retrieve.
Parse
They render what you serve, or fail trying. JavaScript-heavy pages that bots can't execute, bloated markup, and unclear hierarchy quietly exclude you from the training and retrieval corpus.
Chunk
Retrieval systems split pages into chunks and embed them. Clean semantic HTML, direct headings, and self-contained answer blocks survive chunking intact, sprawling pages don't.
Retrieve
When an agent answers, it retrieves chunks, not sites. The machine-readable layer we build, llms.txt, agent feeds, structured endpoints, decides whether your content is retrievable at all.
What's included
IncludedConfigured for machines.
Every engagement sets your machine posture deliberately, then monitors what the crawlers actually do.
Crawler-directive posture
robots.txt rules, llms.txt, and documented handling of AI crawlers, configured per your business rules. Start with the reasoning in our LLM crawler handbook.
Chunk-ready content structure
Semantic HTML, clean heading hierarchy, and self-contained answer blocks that survive chunking and embedding. The classic crawl, index, and schema foundation underneath is owned by our technical SEO architecture.
Agent-ready surfaces
Feeds, structured endpoints, and machine-readable inventory that agents can query directly, instead of scraping pages never built for them.
Retrieval monitoring
Bot-log analysis, citation share, and visibility in answer engines, measured against a baseline so the roadmap iterates on evidence.
How it works
From invisible to retrievable.
A continuous program, not a one-time audit: retrieval behavior shifts, and the posture shifts with it.
01
Baseline
We measure how AI crawlers treat your site today: bot-log posture, llms.txt coverage, machine readability, and citation share.
02
Configure
Directives, content structure, and agent-ready surfaces ship in prioritized sprints.
03
Compound
Monitoring feeds back into the roadmap: what gets crawled and cited gets reinforced, what gets ignored gets reworked.
Before you build.
Questions, answered.
Isn't this just technical SEO? +
Classic technical SEO, crawl, index, schema, performance, is the foundation, and it is owned by our technical SEO architecture practice. Agentic SEO is the layer above it: how AI crawlers and agents fetch, chunk, and retrieve your content, bot directives, llms.txt, agent-ready surfaces, and retrieval monitoring.
How do you measure success? +
Bot-log posture and llms.txt coverage, citation share in answer engines, retrieval coverage of priority topics, and referral traffic from AI systems, all measured against the baseline set before work ships.
How fast do results appear? +
Crawler-directive and machine-readability fixes take effect as bots recrawl; citation share and entity authority compound over quarters. We report from the baseline, not from a timeline.
Make the next move yours.
Tell us where it breaks.
60 questions · 10 infrastructure domains · 12–15 minutes · 0–100 score with prioritized recommendations and a phased roadmap.