LLM visibility, AI readiness audits, Technical GEO

SEO is still the foundation. GEO is the next layer.

Most companies want to “rank in AI” before they fix the basics.

That almost always fails.

AI systems still rely heavily on search indexes, crawlable pages, and structured content. If your technical SEO is weak, your AI visibility will be weak too.

That is why we treat Technical GEO as a staircase:

Strong technical SEO and indexability.
Clear content structure and semantic HTML.
AI-ready delivery patterns (like Markdown endpoints and structured source maps).
Cross-source trust signals that support recommendations.

Skip step one, and everything else gets unstable.

What we audit

1. Crawlability and indexability

We check whether your key pages are accessible, understandable, and indexable by systems that feed both traditional search and AI-grounded answers.

This includes:

robots and crawl directives
sitemap and internal linking quality
URL structure and canonical setup
rendering risks caused by JavaScript-heavy pages

2. Readability for AI parsers

LLMs do not always process pages as well as Googlebot.
Some tools only parse partial HTML or use simplified extraction.

We audit:

HTML size and markup noise
heading hierarchy and semantic structure
content buried in scripts, components, or interactive layers
page sections likely to be skipped in limited context windows

3. AI discoverability infrastructure

We review practical implementations inspired by llms.txt and “Markdown for Agents” approaches.
Not as hype, but as controlled experiments that can improve machine readability in the right context.

We evaluate:

whether an llms.txt file is useful for your site type
how to structure priority pages and docs for AI retrieval
whether a markdown representation should be exposed for agent traffic
server-side rules for delivering cleaner content to automated clients

4. Trust signals beyond your own website

AI does not rely on one source.

It cross-checks what your website says with what appears in other places: reviews, forums, social conversations, videos, and references.

We audit consistency and authority signals across channels so your brand is easier to trust, cite, and recommend.

What we improve after the audit

You get concrete implementation work, not just a PDF.

Typical upgrades include:

technical SEO fixes that unblock crawl and indexing
semantic content restructuring for better machine interpretation
internal linking upgrades that clarify topic relationships
reduced HTML bloat and cleaner rendering paths
implementation of llms.txt where it supports your content model
markdown delivery strategy for agent workflows (when appropriate)
verification checks for how AI tools answer brand and category queries

Platforms we work best with

We feel most at home in:

WordPress and PHP-based websites
React & Next.js
Vue & Nuxt
Astro

We also have deep CMS experience across WordPress, Strapi, Directus, Contentful, and many other platforms.
As a software house, we adapt recommendations to your existing stack instead of forcing a rebuild.

What you receive

AI Readiness Audit with prioritized findings.
Technical GEO roadmap with impact vs. effort.
Implementation plan by sprint.
Optional hands-on delivery by our team.
Re-check after implementation to validate improvements.

The result is simple: your site becomes easier for both search engines and AI systems to understand, trust, and reference.

GEO FAQ

Short answers on AI visibility blockers, audit scope, and implementation path.

Przemek

Yes. GEO focuses on how AI systems interpret and cite your content. But it still depends on strong SEO fundamentals, so we treat them as connected layers.

Usually no. In most cases, strong SEO is the prerequisite for strong AI visibility. Skipping technical SEO creates weak foundations.

Yes, absolutely. This is often a technical issue, not a content issue. Example: One of our clients kept getting a Gemini access error instead of a real-time page content fetching. After a deep code review, we found the root cause was a messy schema implementation (sic!). Once we fixed it, the model could parse the site correctly.

If you have the same problem, we can audit the full chain, from crawlability to parsing and rendering and then fix the exact blocker.

Not automatically. We treat llms.txt as a structured signal and testing layer, not a guaranteed ranking shortcut.

It is a way to expose a cleaner, lightweight version of content for automated systems. It helps most when your HTML is complex and hard for AI tools to parse reliably.

Both. We can deliver a standalone audit, or handle implementation end to end with your internal team.

We work with WordPress, PHP websites, React, Next.js, Astro, Vue, and Nuxt, plus CMS platforms like Strapi, Sanity, Directus, and Contentful. That said, those are just examples. Let us know your stack and we will see how we can help.

Most audits are completed in 1-2 weeks depending on site size, complexity, and number of markets/languages.

Yes. We can work as your technical partner, provide clear implementation tasks, and support your team during rollout.

Scope, site size, platform complexity, number of markets, and whether you need audit-only or audit plus implementation.