Maskwel - Web Development Cyprus

Google measures the real speed of a page with three numbers.

LCP is how long the main part of the page takes to show up. INP is how fast the page reacts when someone taps or clicks. CLS is how much things jump around while it loads.

Sites tend to lose points in the same few places: oversized images, third-party widgets and tracking scripts, fonts and embeds that load without reserved space.

A quick check: run your homepage through Google PageSpeed Insights and see which of the three is marked red.

Builder or custom website? Ask one question first.

Website builders do what they were made for: get a clean site online fast. For a few pages, a portfolio or a simple store, that is often the right call.

Trouble starts when the hard part of your site is not the design. Different access rules for different users. Live calculations. A data structure the template has no slot for.

So what is actually hard about your website? If it is the look, a builder will probably do. If it is the logic behind it, that is usually where a template runs out of room.

We run the same client questions through ChatGPT, Gemini, Perplexity and Claude every month, the way a real client would ask them.

Two numbers come out of that: how often your company gets mentioned, and how often those mentions turn into an actual visit.

Compared against last month, not looked at once and filed away.

Most service pages describe what you do in general terms. An AI assistant reading that has to guess which part answers the question someone actually asked.

A page built around a direct question and a direct answer skips that step. The assistant can lift it as is.

Two companies with similar services can get different results here, and the gap often comes down to which one wrote the answer down first.

We build this into every AIO setup.

What is llms.txt?

llms.txt is a plain text file placed on a website. It gives AI tools a short summary of the business: who you are, what you do, who you work with and where.

Regular pages are written for people, so an assistant has to pick the facts out of them. This file puts the key facts in one place, in a form a machine reads easily.

It works next to good pages and a solid presence on other sources, and we include it in every technical setup.

Where AI looks besides your website

When someone asks an AI assistant who to hire, the answer is not built from your website alone. The assistant also reads what other sources say about your company.

Two companies with equally good sites can get very different answers, because one has a complete, current profile on those sources and the other has a blank or outdated one.

A quick self-check. Search your company name and open the first directory or review profile that shows up. Is the description current? Does it match your website? Are your services listed?

If something is off, fix that first. Which sources matter most depends on your market, and we map them during the AIO audit.

How to check if AI can see your business

A 5-minute check any business owner can run themselves:

1. Open ChatGPT, Gemini, or Perplexity.
2. Ask: “Who should I hire for [your industry] in [your city]?”
3. See if your company appears in the answer.

If it doesn’t, check a second thing: search for your company name plus “reviews” on Clutch, GoodFirms, or Google. AI models pull heavily from these sources when forming a recommendation. A missing or incomplete profile is often the reason a company doesn’t get mentioned.

Run the same test across 2–3 AI platforms. The answers often differ: one model might cite your Google Business Profile, while another might reference a review platform entirely.

If your company isn’t showing up anywhere, the fix is rarely the product. It’s usually the visibility infrastructure behind it.

What we solve with SEO and GEO?

A website can be technically correct and still be invisible in two different ways: absent from Google’s top results and absent from the answers AI models give when someone asks who to hire.

SEO addresses the first problem: page structure, keywords, backlinks, site speed, and the signals Google’s algorithm uses to rank a page.

GEO addresses the second: structured data, third-party validation on platforms like Clutch and GoodFirms, and consistent information across every source an AI model might reference before recommending a company.

Most businesses have invested in one and never touched the other. That gap can send qualified leads to competitors instead, not because the product was worse, but because the AI answer never mentioned them.

We audit both, identify exactly which signals are missing, and fix the technical foundation so a business shows up whether someone types a search query or asks an AI assistant a question.

What is Schema markup and why does it matter?

Schema.org markup is structured data added to a website’s code. It tells search engines and AI models exactly what a business does, who it serves, and where it operates, without requiring them to infer this from page text.

Without it, AI systems have to guess based on unstructured content. Adding Schema markup is one of the fastest technical fixes in an AI visibility audit.

How AIO works?
Google ranks pages based on links, keywords, and site structure. AI models like ChatGPT and Gemini recommend companies differently: they pull from structured data, third-party validation, and how consistently your information appears across platforms like Clutch and GoodFirms.

AIO builds one technical foundation that covers both: the signals Google’s algorithm reads and the signals AI models use to decide who to recommend.