Technical base
Site response, security, protocols, HTTP statuses, and absence of serious access issues.
Methodology
A clear methodology to decide what matters first
AISEO evaluates the web in a specific order. It doesn’t mix everything together. First, it checks if the base is healthy. Then it reviews structure and the ability to guide search engines. Next, it verifies if the site can be validated. Finally, it analyzes advanced AI readiness.
That order matters. Because a useful methodology doesn’t just measure: it also puts everything in its place.
How we work
Four layers, a logical order
The methodology doesn’t just say what is evaluated. It also says in what sequence the site should be understood.
Structure
Website capacity to be crawled and understood through clear architecture and HTML.
Validation
Checking the technical threshold needed to certify or consider the site status reliable.
AI Ready
Analysis of entity, extractability, evidence, and semantic consistency for AI.
Decision Criteria
Methodology isn’t a story. It’s a decision criteria
A useful methodology doesn’t complicate diagnosis. It orders it. AISEO doesn’t mix minor details with critical blocks or treat visual improvements as structural problems.
More order. Better decisions.
AISEO observes real signals, differentiates what blocks site reading from what can be improved, and converts that into a clear roadmap.
The goal isn’t to fill a report. It’s separating what sustains the site from what weakens it. Like a house: check structure first, then decide to paint or upgrade details.
“We don’t review to impress. We review to decide what matters first.”
Criteria
What we look for in each review
It’s not about finding “things.” It’s about knowing if the site communicates, sustains, and leaves reliable activity traces.
Access
Ensuring the site can be visited, crawled, and interpreted without absurd blocks.
Structure
Ensuring a readable document hierarchy and well-resolved internal paths.
Coherence
Ensuring primary messages don’t contradict across pages, snippets, and structured data.
Evidence
Ensuring the site clarifies its evidence, responsibilities, and real context.
Extractability
Ensuring key information can be converted into answers or useful blocks.
AI Readiness
Ensuring the semantic layer truly serves search engines and AI, not just as a visual extra.
Key Principle
Base rules. AI doesn’t substitute it.
This is the heart of the method. AISEO doesn’t use AI as an excuse to forget technical SEO, but as a subsequent layer that only makes sense when the site is ordered and understandable. Check foundations, installation, and structure first; then improve presentation and advanced reading.
Method with Hierarchy
If a site fails access, security, or structure, that’s the priority. Validation and advanced readiness come after.
FAQs
Methodology FAQ
A good methodology doesn’t complicate. It orders.
Why separate technical base and AI Ready?
Because they aren’t the same. A site can be fine in essentials but not ready for AI. Separating them avoids confusing an advanced improvement with a base problem.
Does the methodology work for any sector?
Yes. Content nuances change, but the logic of access, structure, validation, and clarity applies to any serious site.
Is a methodological review just a checklist?
No. The checklist helps, but methodology matters because it orders signals and provides context to the site reading.
What is obtained at the end?
A diagnosis with clear priorities, technical status reading, CertiScore, and an ordered base for deciding improvements, validation, or certification.