We redesigned aiginer.com around how people search today, with AI assistants reading it as much as Google
We've thoroughly reviewed aiginer.com, not just the design, but the way it's written. The reason is simple: more and more people don't reach us by searching on Google and clicking a blue link, but by asking an AI assistant directly. And an AI assistant doesn't link, it answers. If our content isn't built for an AI to understand it, verify it and cite it with confidence, it simply doesn't show up in that answer.
How search has changed
For years, ranking a website meant one thing: showing up among the top results of a search engine for a keyword. That game still exists, but it's no longer the only one. When someone asks ChatGPT, Gemini or Copilot "what is an AI agent" or "how do I automate lead management at my SME", the assistant doesn't hand back ten links: it gives an already-elaborated answer, built from the sources it considers clearest and most reliable. If that source isn't us, another website is having the conversation on our own turf.
This discipline is starting to be called GEO (Generative Engine Optimization) or AEO (Answer Engine Optimization): optimizing not for the classic search engine, but for the engine that generates the answer. It doesn't replace traditional SEO, it complements it. And it demands something quite different: less filler written to rank and more content that answers a specific question precisely, with verifiable facts and no padding.
What we built
Instead of dressing up what already existed, we added reference pieces specifically designed to be citable: content that answers a real question, in full, without needing to read ten more pages to understand it.
- AI Glossary: the terms you'll run into when talking about artificial intelligence and automation (agent, LLM, RAG, embedding, hallucination, AI Act…), explained in plain language, no technical template.
- An `llms.txt` and an `llms-full.txt` at the root of the domain: a structured summary of who we are and what we offer, designed so AI engines can read us at a glance instead of having to interpret the design of the whole website.
Citable content, not inflated content
There's an easy temptation in classic SEO: write more than needed to cover more keywords, even if half the text says nothing new. That approach works worse with a generative engine, which rewards the opposite: precision, clear structure and an answer that can be extracted and cited without ambiguity. That's why every new piece is designed as the answer to a real question someone would ask, not as a generic article with a keyword forced in.
The `llms.txt` follows the same logic. It's a simple text file, at the root of the domain, that summarizes what AIGiner is, what services each division offers and which pages are the reference ones, in a format a language model can read without having to crawl or interpret the HTML of the whole site. It doesn't replace the actual content: it's a map that helps find it.
What doesn't change
This redesign doesn't change who we are or what we offer: it's still the same company based in Barcelona, with the same two divisions (Solutions, AI and automation for a business's day to day, and Labs, creative production with AI) and the same way of working, with a free audit as the starting point and published prices with no fine print. What changes is that now it's easier to find us with the right question, wherever you ask it: in a traditional search engine or in a conversation with an AI assistant.
An example to make it concrete
Imagine someone asking an AI assistant "what's the difference between automating a process and replacing someone's job". Before this redesign, our site didn't have a clear, self-contained answer to that question that an assistant could draw on; the explanation was scattered across several service pages, mixed in with other ideas. Now there's content built exactly to answer that question, fully and verifiably, with links to the Solutions services where it applies in practice. This is a hypothetical search example, but it describes well the kind of question this work tries to capture.
The underlying goal isn't to show up more often, it's to show up correctly: when an AI assistant cites us, it should do so with accurate facts and the same honesty we try to write everything else with. We'd rather be cited less often but precisely, than cited often with nuance lost along the way.
Take a look at the AI glossary.