Everything your site needs to work in both worlds

AI visibility – also called AEO (Answer Engine Optimization) or GEO (Generative Engine Optimization) – is a website’s ability to be read, understood and recommended by AI tools like ChatGPT, Perplexity and Claude. When customers ask AI for “the best X in Bratislava”, the AI answers from sites it can parse and trust: crawler access, structured data, answer-shaped content and third-party mentions decide who gets named. LYVECA builds this layer into every website and offers it for existing sites as the AI Visibility Upgrade (€890).

No – it complements SEO. Classic SEO gets you ranked in a list of blue links; GEO/AEO gets you cited or recommended inside AI-generated answers, where there is often just one recommendation instead of ten results. The fundamentals overlap (crawlability, structured data, good content), so work done for AI visibility usually strengthens classic SEO too.

Because customers are already asking AI instead of Google – and AI gives one or two recommendations, not ten blue links. If AI cannot read your website, you are simply not in the answer: the customer never learns you exist and a competitor gets named instead. Being visible to AI is the new being on the first page of Google – except the recommended business takes almost all of the attention.

An AI agent is software built on a language model that does not just answer questions but takes actions for its user – it can browse websites, compare offers, fill in forms and book services. ChatGPT, Claude and Perplexity are all adding agent modes, which means a growing share of a website’s visitors are no longer people but agents acting on a customer’s behalf.

The agentic web is the web as used by AI agents acting for people: instead of a person reading ten websites, their agent reads them, compares the offers and completes the task – books the appointment or requests the quote. For a business website this changes the job description: it must be readable to agents (structured data, clean content) and ideally actionable by them (MCP), so an agent can choose you and act – not just look.

An agent-friendly website is structured so AI agents like ChatGPT, Perplexity, and Claude can read, understand, and cite it – not just human visitors. This includes AI crawler permissions in robots.txt, Schema.org JSON-LD (structured business data AI engines can reference), answer-shaped content, and llms.txt as a light extra for AI agents and IDE tools. The premium tier adds MCP Server integration, which lets AI agents call the site as a tool – booking meetings, getting pricing, checking availability – without a browser.

Layer 01 is the build layer: custom websites built with AI tools (Claude Code, Next.js) in 5–7 days instead of 4–6 weeks. Layer 02 is the intelligence layer: an embedded AI agent that qualifies leads, answers questions, and books meetings 24/7 without a human. Layer 03 is the visibility layer: making the site readable and citable by AI search engines like ChatGPT, Perplexity, and Claude. Layer 04 is the action layer: an MCP server that lets outside AI agents operate the site directly.

Next.js is a web framework built on React by Vercel – the same technology behind the websites of companies like Nike and OpenAI. We build on it for one main reason: it renders full HTML on the server by default, so AI crawlers and search engines receive the complete content without having to run JavaScript. That matters because AI crawlers (GPTBot, ClaudeBot, PerplexityBot) do not execute JavaScript – a site that assembles its content in the browser is effectively invisible to them. Next.js also gives every build fast load times, optimized images, self-hosted fonts, and lets the whole AI layer – the visibility check, the agent, the MCP server – run in the same project as the site itself.

At minimum the search-facing AI crawlers: GPTBot and OAI-SearchBot (OpenAI / ChatGPT), ClaudeBot and Claude-SearchBot (Anthropic), PerplexityBot, and Google-Extended (Gemini). Many sites block them by accident – security plugins and CDN defaults often treat them as scrapers. If robots.txt has no rules for them they are allowed by default; blocking them removes the site from AI answers entirely.

Schema.org JSON-LD is the machine-readable fact layer of a website – organization, services, real prices, FAQ – that AI engines can quote verbatim. Honest nuance: studies show adding schema alone does not lift citations; it makes you eligible by telling AI exactly who you are and what you sell, so the facts it cites are correct. It works together with answer-shaped visible content, never instead of it.

In 2026 server-log studies the RSS/Atom feed is the endpoint AI bots fetch most – roughly 40% of their requests – because it is the cheapest way to learn what is new on a site. Feeds also carry publish dates, and most AI citations point to pages updated in the last 90 days. Every LYVECA build ships with a feed; this site’s own is at lyveca.com/rss.xml.

MCP (Model Context Protocol) is Anthropic's open standard for connecting AI agents to external tools and data. An MCP server on a website exposes its functionality as callable tools – so an AI agent like Claude can book a meeting, retrieve pricing, or check availability directly, without opening a browser. LYVECA AI offers full MCP integration as Layer 04 (AI-actionable) for €1,890. This very site runs one at lyveca.com/api/mcp – try it.

llms.txt is a plain-text file at the root of a website (like /llms.txt) that summarizes the site for AI tools – the AI equivalent of a README. Honestly: 2026 server-log studies show AI search crawlers barely fetch it yet, so on its own it will not get you into ChatGPT answers. We include it as a cheap extra for AI agents and IDE tools that do read it – what actually earns citations is crawler access, structured data and answer-shaped, citable content.

Yes. LYVECA AI is based in Bratislava, Slovakia, and serves clients globally. All collaboration is remote, in English, Slovak, or Czech.