News and launches

Kit, Web Check and Monitoring: three steps for reviewing what your website says, with the price and the terms in plain sight

Mon, 21 Sep 2026 00:00:00 GMT

From today three things are on sale that until now had neither a shape nor a price: the Compliance Kit, at €49 plus VAT; the Web Check, at €149 plus VAT per website; and Monitoring, at €49 a month or €490 a year, also per website. All three look at the same thing from a different height, which is what your website says today and what the rules ask of it.

One thing is worth saying before going any further, because it shapes everything else: on none of the three pages will you find the figure of a fine. That isn't an oversight. Selling order by waving an amount around is easy and it works, and that's exactly why we'd rather not do it: what you buy here is knowing what applies to you, what doesn't, and in what order to fix it.

Step 1. The Compliance Kit, €49

It comes out of the EU AI Act check, which is still free, still needs no sign-up and still shows the full result: nine questions at most, and hardly anyone sees all nine. The free document tells you what you're missing. The Kit brings the text you have to paste.

The Article 50 notices that apply to you, drafted for your case and with where each one goes.
A one-page AI use policy, with your own details in it.
Five questions for publishing something new without having to run the check again.
The verification record: what you answered, on what date, and against which version of the text.

And its limit, stated before you pay and not buried inside the PDF: the Kit comes from what you answered, not from a review of your website, and it isn't legal advice. One payment, no account and no subscription.

Step 2. The Web Check, €149 per website

Here you're not the one answering: your website is what gets looked at. One site, all of it, in five blocks that always go together and never separately, because half a review gives you a peace of mind that doesn't correspond to anything.

AI notices: that the chat declares itself a machine and that generated content is marked, which is what Article 50 of the AI Act requires.
Environmental claims: "sustainable", "eco-friendly" and the badges, and what sits behind each one.
Accessibility: first whether it applies to you at all, with the article in hand; only then, what you're missing.
The basics: legal notice, cookies and privacy up to date.
AI literacy: what file you'd have to be able to show, and what you're missing to have it.

The environmental block isn't there for decoration. On 27 September 2026 the prohibitions of Directive (EU) 2024/825 on environmental claims start to apply across the Union, and that's the one that separates a statement with something behind it from a nice word on a home page. Spain hasn't written it into national law yet, so what binds here today is the Unfair Competition Act, which already prohibits a claim that misleads.

Every page in your sitemap gets reviewed. If you don't have one, pages are reached by following links from the home page, down two levels and up to 300 pages, and the report says how many it looked at and by which of the two routes. There's no small print about that: it's a figure inside the report itself.

Five working days, and the reason is that somebody reads it

The report arrives in five working days rather than the minute after you pay. The review is automatic, but before it goes out to you somebody at AIGiner reads it and authorises the send. It's the same principle we apply to our agents: what leaves this building with our name on it doesn't leave without someone having read it.

We could deliver in five minutes and it would look better on the page. We'd rather have the five days and be able to answer for every line.

Step 3. Monitoring, €49 a month

A website doesn't sit still. A home page changes, a new banner goes up, somebody publishes an AI-written article without telling anyone. Monitoring repeats the five blocks every month and the reports stack up: that dated file is what you show if somebody ever asks.

Only after a Web Check. The button to take it out sits inside that report.
Per website: each site adds a fee.
No lock-in on the monthly plan: you cancel whenever you like, with no explanations, from the management link in the welcome email and in every report.
If you take it out within 30 days of the Web Check, that review counts as the first report and isn't repeated.
Any month your website can't be reviewed, we tell you before the month is out and that month isn't charged.

Each with its own terms, published today

All three products have, from today, their own purchase terms document, dated and in Spanish and English: the Kit's, the Web Check's and Monitoring's. That isn't paperwork: it's what lets you compare what we promise with what we then do, which is the only way "no small print" means anything.

In the same vein, the AI literacy course for Article 4 is €149 per person, and whoever buys the Kit gets a code that discounts what they paid if they later move up to the Web Check.

What we'd rather not promise you

None of the three leaves you "compliant". There is no official badge certifying compliance with the EU AI Act, and anyone selling you one is selling you something the regulation never created. What you buy here is an automated, dated review that looks at what your website publishes and not at your systems or your contracts, and that doesn't replace a lawyer.

And if what you have is a process rather than a website, this isn't your thing: that gets looked at in the audit, which is still free and still sometimes ends in "there's no point doing anything for now".

Start with the free check, or ask for a Web Check if what you want is the whole site looked at.

We've published our Article 50 transparency declaration, with the table of what still isn't done

Sat, 12 Sep 2026 00:00:00 GMT

There's a sentence that opens our transparency declaration and explains why it exists: Article 50 was already being met by design in what we had published, but it wasn't written down anywhere, and what isn't written down can't be shown. That was the gap, and it's the one this document closes.

It's worth saying straight away what it is and what it isn't. It's a self-declaration, signed under our own responsibility, that can be shown for as long as it's true. Nobody audits it and nobody issues it. It isn't a certificate, not least because for a conversational assistant none exists. It's published in Spanish, at aiginer.com/declaracion-transparencia.

The four obligations, and whose each one is

Article 50 splits obligations between whoever develops an AI system and whoever deploys it, and they aren't the same. We're on both sides: we deploy our own systems on our website and we build systems our clients deploy. The declaration lays them out in a table, paragraph by paragraph, and says which specific thing of ours each one lands on: the website assistant, generated images and video, avatars, and published text.

What we do, and it can be checked

Anyone writing to the assistant on aiginer.com knows from the first message that they're talking to an automated system, and when the assistant can't resolve something it says so and offers a person. There is no point in the journey where somebody gets stuck with a machine.

It doesn't keep conversations either, and that's a design decision rather than an oversight: there's no history to consult, ours or anyone's. The conversation doesn't leave the European Union, and model providers are expressly instructed not to use that data for training.

With dates, not adjectives

The declaration includes a table of next steps, each with its status and its deadline: machine-readable marking of generated content, checking it in our agents widget, and bringing the written breach-notification procedure into the processing agreement. When one is closed, the table is updated and the date is added.

A declaration that only lists adjectives isn't transparency, it's advertising. That's why the table sits inside the document, in plain view of whoever reads it.

What we are not, written once

We aren't certified in anything. Not ISO 27001, not ISO 42001, not SOC 2. We'd rather say it than hint at a process under way.
This isn't an AI Act certification. None exists for limited-risk systems like a conversational assistant. What applies is the transparency obligation, and that's what's declared.
This isn't legal advice. It's what AIGiner does with its own systems.

There's also a point almost nobody gets right and the declaration states: in Spain there is still no penalty regime developing these obligations. Meeting them is mandatory all the same, but anyone selling this by waving the size of a fine around is overstating it.

And a second thing the same day: certificates can be checked

Whoever finishes our course gets a certificate with a serial number, and from today that number can be checked. You type it into the academy's verification page and it says whether it's on record. It's public and it asks for no email and leaves no trace: a certificate only the issuer can confirm isn't much use when the person asking is your own client.

What we ask of whoever deploys a system of ours

When we build an agent for a client, the client is the deployer and part of Article 50 becomes theirs. With every delivery we hand over, in writing, what notice they have to show and where, what gets logged and what doesn't, who the responsible human they appoint is, and the list of providers involved. That isn't an extra: delivering a system without it would be handing someone a problem wrapped in a product.

The principles behind all of this are in our AI policy.

The Article 4 AI literacy course is now on sale and delivers itself, with its own academy

Mon, 07 Sep 2026 00:00:00 GMT

While everyone watched 2 August, there is an obligation in the EU Artificial Intelligence Act that has been enforceable since February 2025 and has gone almost entirely unnoticed: whoever uses AI in a company has to have enough training on what the tool can do, on its risks and on its limits. That's Article 4, and it binds whoever uses AI, not only whoever builds it.

From today, the course that deals with it is bought on the training page and delivers itself. You choose how many people, you pay, and on the same screen you enrol each of them: everyone gets their own academy access and starts whenever they like.

One thing first, because it decides whether this is for you: the course is taught in Spanish. We'd rather say so here than let somebody find out after paying.

Why it lands on you even if you aren't an AI company

This is the part that's hardest to accept, and it's where most companies are exposed right now. Article 4 applies just the same when nobody formally decided anything. If somebody on a team opened a free tool on their own and has been using it with client documents for months, the obligation has been enforceable since February 2025 and not from the day management finds out.

And it asks for appropriate measures, not an exam per person or an accredited level. Documenting them isn't mandatory, but it's exactly what you show if somebody asks. Without paper there's no way to demonstrate anything.

What you get

The course, online and at your own pace, built on cases rather than theory: Article 4 doesn't ask you to know the law, it asks you to know how to use AI.
One seat per person. It isn't a company licence: each employee has their own account, their own progress and their own certificate.
The document kit, already made: an AI use policy, the training record and the Article 4 checklist.
A certificate on completion, with its serial number.

The kit is half the value and it's worth saying so plainly. The course trains people, but what you show when somebody asks is the file: who was trained, in what, when, what use policy is written down and who answers for it.

What we won't promise you

There is no official AI Act compliance badge, not for training and not for anything else. The regulation never created one. Our certificate evidences that this person took this course, with a date, and that's everything a certificate issued by us can evidence.

Nor are we going to tell you the course settles the matter. Article 4 is one piece; Article 50, the one about notices, is a different one and gets resolved elsewhere. If you want to know which ones land on you before buying anything, the check is free and gives the full result without asking you to register.

An example to make it concrete

Imagine an eight-person accountancy firm where three people use an AI assistant to draft emails and summarise client paperwork. Nobody decided it, it simply happened. With the course, those three are trained in an afternoon, the firm ends up with a one-page policy saying what may and may not go into that tool, and with a dated record of who was trained. It's a hypothetical example, but it describes well the situation most of the practices we talk to are in.

And a decision about how it's delivered

The academy lives on its own site, separate from the website, and access is granted immediately without anyone on our side having to step in. It's the first thing we sell completely automatically, which is why it was tested with real purchases before opening: a flow that sends emails isn't tested until a real email goes out.

See what's included at AI training.

AIGiner is now a limited company: what changes for anyone working with us, and what doesn't change at all

Tue, 01 Sep 2026 00:00:00 GMT

Since 1 September 2026, AIGiner is AIGiner, S.L., a limited company registered with the Barcelona Companies Registry. The full registry details, with the exact name, the tax ID and the entry number, are where they should be and can be checked: in the legal notice and at the foot of every document we sign.

This is the sort of news a company usually announces with a photo and a couple of adjectives. We'd rather set out what actually changes, which is little but not trivial, and what doesn't, which is nearly everything.

What changes

Who signs. A contract, a data processing agreement or a confidentiality agreement is signed with a company identified in a public registry, not with an individual.
Who answers. Liability for what we deliver sits with the company, and that's checkable by anyone who wants to look before signing.
How invoicing works. Everything is issued in the company's name, with its tax ID, and tax is calculated according to who is buying and from where.

Why we're telling you, if it's paperwork

Because the question underneath isn't paperwork. When a small business or a professional practice lets a third party touch a process that feeds it, or its clients' data, the first thing it needs to know is who it's dealing with and who it can turn to. That question now has an answer that doesn't depend on trusting us: it's in a public registry.

It's the same idea holding up everything else we do. A commitment that only exists in a sales conversation is easy to soften later; one that's written down, dated and in a place anyone can consult isn't.

What doesn't change

Not the team, not the two divisions, not the way we work. Solutions still brings AI and automation to the day-to-day running of a business and Labs still brings that same technology to brand communication. The initial audit is still free, prices are still published on the website, and every project's scope is still closed in writing before we start.

Nor does what we've decided not to do change: we still have no client we can name on the website, we still have no certifications, and we still say so. A registered company evidences nothing about the quality of a piece of work, and we aren't going to use it as if it did.

Where everything checkable lives

The legal section holds the legal notice, privacy, cookies, terms and the conditions for each service, each with its own date. The AI policy holds the six principles we apply, the uses we refuse and the real limitations of the technology, which is the part almost nobody publishes.

We'd rather all of that could be read without booking a call. People who take the trouble to look before writing the first email tend to be exactly the kind of client who is best to work with afterwards.

Meet the team and the story at About us, or write to us at Contact.

We audited our own EU AI Act check against the text of the regulation, and it went from five questions to nine

Mon, 17 Aug 2026 00:00:00 GMT

We publish a free check so anyone can find out what the EU Artificial Intelligence Act requires of them. We've now run the whole thing against the text of the regulation again, article by article, and a new version has come out of it: where there were five questions there are now nine, even if hardly anyone sees all of them, because the path gets shorter as soon as it's clear what doesn't apply to you.

We're writing about it because the result of that review is more interesting than the change itself. A compliance check that gets things wrong isn't neutral: it reassures the people who shouldn't be reassured, and that does more damage than having no check at all.

What was missing from the questions

The new questions aren't padding. Each one exists because without it the result could come out wrong in a perfectly ordinary case.

Whose the chat on your website is. One you built isn't the same as one you bought that introduces itself with your name and your brand: the notice that there's a machine behind it belongs to the deployer, and that shifts case by case.
What your images, videos and voices are like. Whether they're realistic or clearly illustrations, because that's what decides whether a disclosure is needed.
What your AI-assisted text is about. The regulation separates your own company's communications from information of public interest, and it doesn't ask the same of the two.
What you have in writing. A use policy, a training record, an inventory of where AI sits, reviewed supplier contracts. That's what you show if somebody asks.

Three rules that don't get touched when writing it

A check like this can be written in many ways and nearly all of them are worse. These three are written into the code itself, so they don't get lost when somebody edits it six months from now.

It never says "you comply" or "you don't comply". It says which obligations apply and whose they are. A nine-question form is in no position to certify anything.
No figure for a fine appears. Not one. What's on offer is order and control, not fear.
No badge is promised. No official one exists, and pretending otherwise would be exactly the problem we're trying to solve.

And the part people thank us for: what doesn't apply

The result isn't only a list of duties. It also says which obligations don't land on you and why, with the reason alongside. That sounds like a minor detail and it isn't: a good part of the alarm going around consists of attributing to a small business obligations the regulation reserves for whoever builds models or deploys high-risk systems. Knowing what doesn't apply to you is what stops it being sold to you.

Free, complete and with no sign-up

The full result appears on screen without asking for anything: no email, no account, no "leave us your details to see the report". You can have it by email if you want, but that's your decision and not a toll. It takes about two minutes and it isn't legal advice, which the page also says before you start.

If there are terms you don't recognise when you finish, the AI glossary explains them in plain language, with no technical boilerplate.

Run it yourself at the EU AI Act check. Nine questions at most, and the result shows in full.

TheHumanBehind: a registry so that an avatar, a voice or an agent created with AI has a named person behind it

Sun, 02 Aug 2026 00:00:00 GMT

Millions of avatars, voice clones and AI-generated images are born every day, and not one of them is tied to anybody. While everything goes well you don't notice. The problem shows up the day something goes wrong, when somebody impersonates another person, uses a character commercially without owning it, or publishes a copy that surfaces before the original: that's when you find out there's nowhere to point, because nothing anywhere records who answers for what.

Today that absence is more obvious than ever, because today Article 50 of the EU AI Act becomes applicable. The law requires you to say that something is AI-made, but it doesn't create any portal or database where you can evidence who is behind it. That gap between what you're required to declare and what you can actually prove is exactly what we've tried to fill.

What it is

TheHumanBehind is a trust registry. You register an avatar, a voice clone, an agent, an image, a video or a piece of music, and that content gets tied to you with a date and with a fingerprint that identifies it without anyone having to store the original file. That fingerprint works as proof of precedence, so if a copy turns up tomorrow you can show yours already existed, with a date you didn't set yourself.

The brand's claim sums it up better than any paragraph we could write: the right to authenticity, the proof of your worth.

And what it isn't

We're putting this up here rather than in a footnote, because it's the sort of precision that deserves to be read before registering anything.

TheHumanBehind is an independent, voluntary registry. It isn't an official EU registry, and registering doesn't by itself fulfil any legal obligation. It's simply the public place that keeps on record who answers for an avatar.

There is no badge certifying compliance with the EU AI Act: the regulation never created one. What can exist, and is what we've built, is a dated place recording that something is yours and that you're the one standing behind it.

Two tiers, and one decision about what's visible and what isn't

Registered. Free and available now. It's a dated self-declaration along the lines of "this is mine and I take responsibility for it", which leaves you a dated record and a fingerprint of the content.
Verified. Not open yet. An external provider checks there's a real human behind it, and at the professional tier it also checks the qualification when the matter touches health, money or the law.

The underlying decision has to do with what's visible and what isn't: the free tier is private, with no public page, no search and no API, because we think of it as your record and nobody else's. Public begins at the verified tier, and it doesn't stop half way there, since it includes a consultable profile, a search and an API open to anyone.

A directory full of unchecked entries doesn't evidence anything, because anyone can register anything. That's why we'd rather what surfaces publicly is only what somebody has bothered to verify.

Looking someone up is free, always

Checking whether somebody is verified will be free for anyone and with no time limit, and we're saying that as plainly as we say everything else. A registry only works as a reference if anyone can look it up, and that's why looking it up is free. The terms of verification will be announced before it opens.

Why we're the ones building it

Because we've spent months in this conversation from the other side. At Labs we produce AI video and characters, and on every job the same awkward question ends up coming round about whose this is and who answers if somebody uses it where they shouldn't. At Solutions we build assistants and automations, and the question is the same one in a different suit, because there too somebody has to answer for what the machine says.

A registry doesn't fix the underlying problem and we're not going to pretend it does, because it doesn't stop anyone cloning a voice or using it wherever they like. What it does is make sure that, when that happens, there's a dated place recording that the voice was yours. Nothing like that exists today, and it's the difference between having an argument and having evidence.

Where it stands

The free registry is built and running. Verification isn't open yet. It's a young project and we're describing it as one, because we'd rather you tried it knowing what's finished and what isn't, instead of running into the gaps on your own after being sold the whole thing.

You can register yours for free at thehumanbehind.com.

From today Article 50 requires you to say what is AI-made. What it doesn't say is who answers for it

Sun, 02 Aug 2026 00:00:00 GMT

Today, 2 August 2026, the EU Artificial Intelligence Act reaches general application, and with it comes Article 50, which is the one that touches almost every company however small. The law demands transparency about AI-generated content, and that includes visibly disclosing deepfakes.

It's a rule about telling people rather than about audits, and that's precisely the awkward part: most of its obligations are met with two well-placed sentences, but only if you know those obligations are there at all.

What it requires

The rule requires a chatbot to state that it's a machine, clearly and on first contact, not in the small print and not once the conversation is five messages deep. Calling it an "assistant" isn't enough, because anyone can read that as a person on the other end.
Content generated or edited with AI has to be identified, whether it's text, images, video or voice. There's a nuance people forget here, which is that when an agency generates it but another company publishes it, the obligation falls on whoever publishes.
Deepfakes get disclosed on first exposure, meaning where they're seen and not in a footnote nobody reads.

The only exception is common sense, because if it's obvious to anyone that this is a machine you don't have to keep saying it. It's worth remembering that "obvious" is quite a high bar, though, and that when in doubt it's always cheaper to disclose than to argue about it later.

And now, the half nobody tells you

This part gets explained far less, and yet it's half the picture. Three ideas are going around about this regulation that simply aren't true.

You don't have to register your chatbot anywhere. The EU database is for high-risk systems, and an assistant that answers frequently asked questions isn't one, so there's no portal to sign it up on even if you wanted to.
Using AI doesn't make you an AI provider. If you buy a tool and use it, your obligations are a deployer's, and they're far lighter than a builder's. Confusing the two roles is the source of much of the alarm going around these days.
The €15 million figure is going around a lot these days, but the regulation reserves it for its most serious infringements and doesn't attach it to a missing notice on a chat. It's worth reading the penalty regime before assuming it applies to any case.

The gap it leaves

Here's the interesting part, and it's the part that has been discussed least these days. The regulation requires you to declare that something was made with artificial intelligence, but it doesn't require a record of who is behind it and, more to the point, it doesn't create any portal, registry or database where you could put that in writing.

So Article 50 can be complied with to the letter, labelling a video and disclosing a chatbot, and there's still nowhere to point the day somebody clones a voice or publishes a copy before the original. Transparency about the what doesn't answer the question of the who, and that question is left without anywhere to be answered.

That gap is what we're trying to fill with TheHumanBehind, a registry where what you create with AI is tied to a person with a date and a content fingerprint. It's worth being clear that it's a private, voluntary initiative, that it doesn't replace anything the law requires, and that it doesn't by itself evidence any legal compliance: all it gives you is a dated place recording who's standing behind something.

An earlier obligation almost nobody has looked at

While everyone watches today's date, something has been enforceable since February 2025 and has gone almost entirely unnoticed: the regulation requires whoever uses AI in a company to have enough training on what it can do, on its risks and on its limits.

And it applies just the same when nobody formally decided anything, which is where the real problem sits. If a team opened a free tool on their own and it has been in use for months with client documents, that obligation has been enforceable since February 2025. It's by some distance the place where most companies are exposed right now.

We ran that review on our own site and found what you'll probably find too, because the assistant introduced itself as "customer support" and that reads like a person. It now says in the header, in the greeting and even on the button label that it's an artificial intelligence and not a person, and fixing it took an afternoon.

In the free audit we go through how you're using AI today and what could be improved.

Why our agents ask permission before the actions that matter

Tue, 28 Jul 2026 00:00:00 GMT

This year's story is autonomy. Agents chaining tasks together, opening their own browser, writing into your systems and closing the loop without anyone looking over their shoulder. The technology really is arriving.

The question still to be answered is what happens on day forty. And there, in the projects we've built ourselves, what separates a striking pilot from something still running months later has nothing to do with how powerful the model is, but with where you decided to put the handbrake.

The problem isn't that it gets things wrong, it's how fast

A person who enters a figure wrongly makes one mistake and, with a bit of luck, somebody catches it that same afternoon. An agent that enters it wrongly makes the same mistake four hundred times before lunch, without tiring and without setting off any alarm, because from inside the system everything looks fine: tasks complete, the queue goes down and the logs say it's done.

That's why the useful question when you're designing an automation isn't whether the agent can do something on its own, since it almost always can. The question that actually matters is what would happen if it did it wrongly five hundred times in a row. If the answer is that you fix it in ten minutes, go ahead; if the answer is that you're calling two hundred customers to apologise, that's where a human approval belongs.

Where we draw the line

It isn't an abstract principle that shifts from project to project, but a list we apply the same way every time and put in writing before we build anything.

Alone, without asking: reading, classifying, summarising, drafting or moving information between internal systems. Everything that's reversible and doesn't leave the building.
With human approval: anything that goes out with your name on it, touches money, deletes something or writes into a system other people depend on. An email to a customer belongs here, and so does an invoice.
Never, even if it technically can: deciding about a person, whether that's screening a CV or scoring somebody's creditworthiness. The EU regulation classes it as high risk.

Asking permission doesn't mean approving things all day

That's the usual misunderstanding and it's a fair worry, because if every step needs signing off then you haven't automated anything, you've just swapped one job for another. The trick is that the agent arrives with the work done right up to the last click: it drafts the whole email, prepares the whole invoice and leaves the reply ready, so all it asks the person for is a yes or a no with the consequence in plain sight.

In practice that turns an hour of work into two minutes of review, which is where nearly all of the saving is, and in exchange it rules out the one scenario that genuinely hurts, which is something going out with your name on it that nobody looked at first.

What this has to do with this week

Quite a lot, which is why we're writing it now. Article 50 of the EU regulation becomes applicable these days, requiring you to say when there's a machine behind something. It's the same idea seen from the legal side, because however autonomous the system is there's always somebody who answers for what it does, and that somebody has a name.

An agent that asks permission on the sensitive things isn't a less capable agent, it's one where you know exactly where the signature is.

What we'd rather not promise you

We aren't going to tell you full autonomy won't arrive, because it probably will and sooner than we think. What we're saying is that today, with what exists, building an automation with no control points amounts to betting that nothing odd will happen for months, and when it does, the cost ends up being paid by the client.

So we'd rather start with the boring version, handbrake where it belongs, and take it off later once we've watched the system run for a few weeks. It looks less impressive in a deck and considerably better in March.

Got a process in mind and no idea where that handbrake would go? We'll look at it together in the free audit.

aiginer.com is now also in English: the whole site translated, with an address of its own

Tue, 21 Jul 2026 00:00:00 GMT

aiginer.com is now available in English. The whole site (home, Solutions, Labs, services, industries, documentation and legal pages) has its mirror at `/en/`, with its own routes in that language, not a surface-level translation pasted over the Spanish pages. The industries section lives at `/en/industries`, Labs at `/en/labs`, the documentation at `/en/docs`, and so on for every part of the site: whoever enters in English stays in English for the whole visit, from the home page to the contact form, without switching languages halfway through.

Why now

We are an artificial intelligence company, and a good part of the people searching for AI and automation solutions online do it in English: because they work with clients outside Spain, because the sector's reference content is mostly written in that language, or simply because it's the language they use to evaluate providers before writing the first email. Staying Spanish-only meant leaving that audience out, even when it fit perfectly with what we offer. A company dedicated to bringing technology within reach of any business cannot, at the same time, shut itself off from half the language in which that technology gets discussed.

How to choose a language

The language selector lives in the footer, with Spanish and English always visible, on any page of the site. The site also automatically suggests a language based on the country you're visiting from: if it detects you're not coming from a Spanish-speaking country, it offers to switch to English with a discreet notice you can accept or dismiss, which won't show again once you've decided.

That suggestion relies solely on the network signal we already use to serve the page, with no third-party cookies or external scripts, so it doesn't need any extra consent to be shown. It's a small detail, but it matters: we'd rather not build a tracking system just to decide which language to greet you in.

Legal pages, actually translated

The English mirror also covers the legal pages: legal notice, privacy, cookies, terms and the rest of the documents have their translated version, not just a summary. That way, an international client, partner or supplier can read, in their own language, exactly the same conditions that govern the Spanish site, without relying on an external translator or an incomplete version that leaves out the terms that actually matter.

The documentation, also in English

The public documentation we gathered at `/docs` (close to fifteen pages about who we are, how we work, our services catalog, the stack we build with, security and data handling, and the full catalog of our AI agents) now has its English version at `/en/docs`. That information used to be scattered across several pages and a separate product panel; now it's a single point of reference, in both languages, for anyone who wants to understand in detail what we do and how we do it without depending on a sales call to find out.

What stays in Spanish

News is available in English as well: every announcement is translated with the same care it was written with, because that is where we explain how we work and why we make the decisions we make. The mirror is complete, with no corner of the site left behind in Spanish.

An example to make it concrete

Imagine a company based outside Spain evaluating automation providers for its subsidiary, wanting to understand, before writing a single email, how we work and what guarantees we offer. With the site only in Spanish, they would have to rely on an automatic translator to read the legal terms or the services catalog, risking losing nuance in a document that binds both parties. With the site in English, they can read exactly the same content, with the same precision, in the language they make their decisions in. This is a hypothetical example, but it describes well the kind of conversation this change makes possible.

Switch languages from the footer of any page, or go straight to the English home page.

AI guides by industry: 17 sectors, each with its own bottlenecks and the automations that fix them

Tue, 21 Jul 2026 00:00:00 GMT

We're launching /industries, a new section with automation guides for each sector. Instead of talking about AI in the abstract, every guide gathers the real pain points of a specific sector and the automation cases that solve them, along with the AIGiner services that best fit each one.

17 sectors, with concrete cases

There are now guides for 17 sectors, including Real Estate, Legal, Retail and Fashion, Tourism and Hospitality, Healthcare and Medicine and HR and Recruitment, in addition to finance, e-commerce, logistics, education and others.

In Real Estate, how to automate instant replies to leads from listing portals, automatic qualification and viewing coordination.
In Legal, how AI reviews and compares contracts, flagging what changed against the firm's standard template, and how it enables natural-language search across case files.
In Retail and Fashion, Tourism and Hospitality, Healthcare and Medicine and HR and Recruitment, equivalent guides with their own pain points and use cases.

Each guide links to the specific Solutions (and, when it applies, Labs) services that solve those cases, so it's clear at a glance what you can ask for today without reading the whole catalog. Every sector also has its own FAQ section, with the questions businesses in that sector actually ask before automating anything.

This isn't generic content with the sector's name swapped in: every guide starts from the real pain points businesses in that sector tell us about when we talk to them, and it details what to automate first, not a long list of possibilities with no order of priority.

Why by industry and not in the abstract

Talking about "AI for businesses" in generic terms sounds good but doesn't help anyone decide anything: every sector has its own bottlenecks, its own vocabulary and its own urgencies, and a guide that works equally well for a real estate agency and a law firm, in practice, doesn't fully work for either. That's why we chose the slower path: writing sector by sector, based on what businesses actually tell us when we talk to them, instead of a list of recyclable use cases with the sector's name swapped in at the start of each sentence.

The rest of the catalog also covers Finance, E-commerce, Logistics, Education, Construction, Restaurants, Consulting, Manufacturing, Insurance, Automotive and Nonprofits and the third sector, among others. A few examples of what you'll find in those guides:

In Finance, how to automate transaction reconciliation and the recurring reports that today get built by hand every month-end close.
In E-commerce, how to automatically answer the repeated questions about orders, returns and warranties, leaving a human agent only the cases that truly require judgment.
In Logistics, how to track shipment status and flag issues before the customer has to ask about them.
In Education, how to manage enrollment queries and the repeated questions of every admissions cycle without the academic team having to answer the same thing a hundred times.

An example to make it concrete

Imagine a tax advisory firm that receives dozens of similar questions from clients every quarter about deadlines, pending documentation and case status. Its sector guide doesn't propose "automating with AI" in the abstract: it points out that this flow of repeated questions is the first candidate, with an agent that answers frequently asked questions and leaves the team only the cases that truly need professional judgment. This is a hypothetical example, but it's exactly the kind of concrete recommendation we aim for in every guide, instead of a list of possibilities with no order of priority.

The guides will keep expanding with new sectors and more cases within the ones that already exist, following the same criterion we always apply at AIGiner: start from the business's real problem, not from the technology we want to sell.

This section is built on the same principle that guides the company's two divisions: in Solutions we automate a business's day to day, and in Labs we bring that same technology to brand communication. That a law firm needs different things from a real estate agency or a retail brand isn't a minor detail, it's exactly what makes a recommendation genuinely useful instead of generic advice anyone could repeat.

Check your sector's guide in Industries, or request a free audit if you'd rather have a direct conversation.

What it means that there's no fine print at AIGiner: no lock-in and a closed price before we start

Mon, 20 Jul 2026 00:00:00 GMT

"No fine print" shows up in almost everything we write, and it's easy for it to sound like a closing line, one of those phrases people tack on at the end because it sounds good. For us it isn't: it's a concrete list of commitments that can be verified, not an empty promise. Here we break it down, point by point, so you can check it against what we actually do.

Our commitments, one by one

These are the concrete commitments, one by one:

We tell you what the diagnosis says. If your free audit concludes that AI adds little value in your case, we tell you with the same clarity as if it added a lot.
The price is closed before we start. After the audit you receive a fixed written quote, with the scope detailed, and you decide with the number in front of you.
We work with no lock-in. If something stops adding value for you, you can cancel it. We'd rather earn the renewal every month.
We state the real status of every service. If something is in beta or has limits, we say so, as a beta with its limits, not as a finished product.

Why it costs us more

Being this direct has a real cost, and it's worth saying: some free audits end in "it's not worth doing anything for now", and that report costs us the same time as one that does turn into a project. Some sales fall through because we mention a limitation before anything gets signed. We accept it because the alternative (always saying yes, promising more than can be delivered) builds a relationship that breaks the moment the first surprise invoice or missed deadline shows up.

We'd rather grow slowly, with clients who trust what we say. It's a long-term bet, not a campaign slogan.

An example to make it concrete

Imagine an SME that asks us for an audit because it thinks it needs to automate its entire invoicing. When we review the process, we see the volume is so low that the actual savings don't justify the cost of building and maintaining the flow, at least for now. We tell them that plainly, with numbers, instead of selling them a project we could technically build but that wouldn't be in their interest. Months later, when their volume grows and the math changes, we're still the ones they call, because the first time we told them the truth even when it wasn't convenient for us.

That's the substance of "no fine print": it's not that there are no conditions, it's that whatever conditions exist are in plain sight, explained before anything gets signed, and don't change once you've already trusted us.

How it applies in each division

The principle doesn't change based on the project, but it shows up differently depending on which side of AIGiner you're talking about. In Solutions, it means every agent or automation is delivered with its scope in writing, what it does and what it doesn't, and with sensitive actions that always go through human approval. In Labs, it means every campaign or creative piece is approved before publishing, and that the rights to what's produced belong to the client from day one, with no recurring fees or conditions that appear after signing.

Why we write this down instead of just saying it on a call

A promise that only exists in a sales conversation is easy to forget or walk back later. That's why we'd rather leave it written down, on a public page, dated, so anyone can come back and read it a year from now and check whether we're still doing what we said. If we ever stop honoring it, let there be a record that we said it and didn't uphold it, instead of the promise fading into the memory of a meeting.

This is also a form of internal accountability. When a principle is written down and public, it doesn't depend on the mood of whoever's explaining it on a given call: it becomes a standard the whole team, in any division, has to respect the same way.

Check it for yourself with a free audit.

What a black-box AI is, and how we work so every decision can be explained

Sun, 19 Jul 2026 00:00:00 GMT

There's a question we should ask ourselves more before letting an AI touch anything that matters: if someone asks tomorrow why it did what it did, do we have an answer, or just a guess? A black-box system has no answer: it hands back a result and that's it, with no trace of how it got there. That might be fine for a draft with no consequences. It's not fine for anything that touches money, customer data, or a decision that needs to be defensible later.

What we mean by black box

We call any system a black box when it acts without leaving a record of what it did, with what information and under what criteria. It's not a problem with the technology itself, it's a design problem: you can build an AI agent that explains every step, and you can build one that doesn't. The difference is a decision, not a technical limitation.

The risk of a black box isn't just that it gets something wrong, any system gets things wrong sometimes. The risk is that, when it does, no one can reconstruct what happened. Without that trail, you can't fix the pattern that caused the error, you can't explain it to a client and you can't defend yourself if someone asks. A tool that can't be audited leaves that question unanswered, no matter how well it talks.

How we solve it

We apply the same principle to everything we build, from a simple automation to a full platform of agents by department: every relevant action gets logged, with what was requested, who approved it and what information the decision was based on.

Audit trail: what each agent did, when and with what data, available to check at any time.
Human approvals before any sensitive action: nothing executes behind your back.
Internal redaction: the technical details of how the system works don't leak into the responses, but the result is always traceable backward.
Explainability, not guesswork: if an agent proposes something, you can see what it based it on, not just the final result.

Imagine a law firm that uses an agent to review contract clauses and flag ones that fall outside the usual pattern. Months later, a client asks why a specific clause was approved. With a well-built audit trail, the answer is right there: what the agent reviewed, what it flagged, who validated it and when. Without that record, the answer would be "we don't know", and that phrase is unacceptable when something important is at stake.

A principle, not a box to tick

It's easy to turn traceability into a compliance requirement solved with a technical log nobody reads. That's not what we're after. For us, a system being explainable means that anyone on the client's team, not just whoever configured it, can look at the history and understand what happened, without needing help to interpret it. A log only the person who wrote it can understand doesn't solve the problem: there's still a black box, just with a nicer presentation.

That's why, when we design a flow or an agent, the question "how will whoever uses this in six months explain it?" gets asked as early as "what does this need to do?". It's not a later step tacked onto the end of the project: it shapes, from the start, what information gets stored and how it's presented.

What this means for anyone working with us

In practice, this translates into something very concrete: you'll never have to blindly trust a Solutions agent because "that's just how AI works". You'll be able to request the history of any action, understand it without outside help, and use it, if needed, to justify a decision to a client, an auditor or your own team. That principle, along with the rest of our security and data-handling practices, is detailed on our security and best practices page.

We don't believe AI has to be perfect. We believe it has to be accountable for what it does, and that's only possible if it can be explained. That's why we'd rather build a system that's somewhat slower to put together and fully traceable.

Talk to us about your case at Contact.

Automating isn't replacing anyone: what the difference is and how we apply it in every project

Sat, 18 Jul 2026 00:00:00 GMT

Every time we talk about automation with a new client, the same question comes up without quite being said out loud: "does this mean I'll need fewer people?". It's a reasonable question and it deserves a clear answer. The short answer is no. The long answer is the one that actually matters, and it's the one we try to explain here.

Two words that get confused

Automating and replacing are sometimes used as synonyms, but they describe very different things. Replacing means a task a person used to do is now done by a machine, and that person is no longer needed. Automating, as we understand it, means a repetitive task stops taking up a person's time, so that person can spend their time on something that does need human judgment. The task disappears from the day to day; the person doesn't.

The confusion comes from the fact that, sometimes, the first thing does happen: there are processes so mechanical that, once fully automated, the role that existed solely to do that no longer makes sense. We don't deny it or hide it. But in the vast majority of the cases we work with, the reality is the opposite: the problem isn't too many people, it's not enough time. Automating a task doesn't leave anyone without a job, it gives them back hours for the work that actually mattered and had been postponed for months.

How it shows in practice

This isn't an abstract idea, it shows in every project we deliver:

An accounting firm that automates invoice sorting doesn't lay off the person who managed them: that person goes from typing in data to reviewing exceptions and helping clients who call with questions.
A real estate agency that automates the first reply to a lead doesn't do without its sales rep: it lets them come into the call with the context already prepared, instead of losing the morning sorting the inbox.
A repair shop that automates appointment reminders doesn't eliminate anyone at the front desk: it frees that person to take good care of whoever is in front of them, instead of being tied to the phone.

Where we draw the line

The principle we apply to every flow is the same one that governs everything we build: the machine is a copilot, not an autopilot. We automate what's repetitive, what follows clear rules and doesn't demand subjective judgment. What does require judgment (deciding, negotiating, taking care of a client at a delicate moment) stays where it should, in a person's hands. And for sensitive actions, the flow pauses and waits for human approval before executing.

Imagine an advisory firm that automates sending reminders about pending documentation to its clients. The system detects who's missing something, prepares the notice in the firm's usual tone and leaves it ready. It doesn't send it on its own: someone on the team looks it over, adjusts whatever's needed and hits send. The tedious part (checking client by client, writing the same message thirty times) disappears. The relationship with the client, which is what truly matters, remains a human matter.

Why we bring it up from the start

We could avoid this conversation and let each client form their own idea of what automating means. It would be more comfortable in the short term. But we'd rather say it upfront, because it's the only way for a company's team to genuinely collaborate on an automation project, instead of putting up obstacles out of fear over something that wasn't explained properly. A flow built with the team's suspicion behind it rarely ends up getting used; one built with the team on board, understanding what it will and won't take off their plate, gets adopted and gets maintained.

How the day to day changes, not just the process

The clearest effect isn't in the automated process itself, but in what the person does with the time they get back. In our industry guides we gather concrete examples, sector by sector, of where that recovered hour usually goes: taking better care of the customer in front of you, reviewing a complicated case more calmly, or simply not going home feeling like you spent the day putting out the same fires over and over.

This doesn't mean automating has no impact on how a team is organized. Sometimes it does: a task that used to take up half a person's day can end up taking ten minutes of review. What we don't accept is the idea that this freed-up time is, by default, surplus time. There's almost always valuable work waiting right behind the repetitive task that gets automated, and our job is to bring it into view.

Tell us which process steals the most time from you at Process Automation, or start with a free audit.

We redesigned aiginer.com around how people search today, with AI assistants reading it as much as Google

Wed, 15 Jul 2026 00:00:00 GMT

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.

The Labs catalog, in full swing: from avatars to the complete campaign

Sun, 05 Jul 2026 00:00:00 GMT

AIGiner Labs has been running for months and the catalog is now well established, so it's time to take stock of what you can order today. This isn't a launch announcement: it's a snapshot of a division in full swing, with a proven way of working and a range of formats that covers everything from a single piece for social media to a complete campaign with its own art direction.

What you can order today

The catalog has grown based on what our actual projects have asked for, so it isn't a closed list of standalone services, but a set of formats that combine according to what each brand needs:

Vertical Reels and TikToks for social media, designed for the format people actually consume today.
Instagram carousels and recurring content pieces, so you never draw a blank week after week.
Ads for Meta and Google Ads generated with AI, with art direction and no filming cost.
Virtual avatars and spokespeople, unique to each brand, that record whatever you need whenever you need it.
Virtual influencers with their own identity, consistent over time.
Video and interviews, audiovisual production ready to publish.
Campaigns with streamers and actors, when the project calls for a real human face alongside the AI-generated pieces.
Creative websites, built on the reusable design system that was born from Labs' first project.

Why it works this way

Four things explain why this model works better than traditional filming for a small or medium business:

Production in days, not weeks: no filming, no long waits, from idea to finished piece in short timeframes.
Brand consistency: same face, same voice, same style across every channel, so the brand is recognizable wherever it appears.
Scale without limits: one creation can become infinite variants (formats, languages, versions) without multiplying the work from scratch each time.
Clear rights: everything produced belongs to the client, with no recurring fees or third-party rights involved.

How we work, step by step

The method hasn't changed since the first project, because it's what guarantees that speed never eats into creative control:

Briefing and art direction: we understand the brand, the audience and the goal, and define the campaign's creative direction.
Concept: we design the concept and script, and present them before producing anything.
Production: we create the pieces combining talent, AI and art direction, in every format needed.
Review and adjustments: we iterate with the client until every piece fits their brand and goals.
Delivery and scaling: everything is delivered ready to publish and, if needed, scaled into variants connected to the client's workflows.

An example to make it concrete

Imagine a cosmetics brand that needs a constant social media presence but has no in-house content team. Instead of booking a monthly shoot, a virtual influencer is defined with the brand's identity: a face and a tone that repeat in every piece. From there, carousels, reels and ads with that same character go out every week, without setting up production from scratch each time. If the campaign also calls for a human face for a specific launch, a streamer or actor is added for that one-off piece. This is a hypothetical example, but it reflects well how the catalog's formats combine today.

As with everything AIGiner does, speed doesn't replace judgment: every piece is reviewed and approved before publishing, and creative direction remains human from start to finish.

See the full catalog and formats at AIGiner Labs.

We launch the AI Phone Assistant: 24/7 support that qualifies, books and never leaves a call unanswered

Thu, 04 Jun 2026 00:00:00 GMT

We're introducing the AI Phone Assistant: a natural voice that answers your calls 24 hours a day, 7 days a week. It answers, replies to frequently asked questions, qualifies the caller and routes them to the right person when needed. It's not an answering machine or a recorded menu: it's a real conversation, designed so whoever calls hangs up with their question resolved or an appointment on the calendar.

Every missed call is a lost customer

For most businesses, the phone is still the first door. But no one can answer at all hours, and a call that goes to voicemail rarely gets returned. Someone who calls and gets no answer usually doesn't try again: they call the next name on the list. The assistant makes sure no one goes unanswered: it picks up on the first ring, at any hour, with no queues or waiting.

The problem gets worse at peak times, which are exactly the worst moments to miss a call: lunchtime, late afternoon, a campaign spike or a day when the team is overwhelmed. That's where opportunities slip away, and that's where having a voice that always picks up makes the biggest difference.

It's not a "press one" menu. It's a real conversation: it understands what's said to it, responds naturally and knows when a case needs a person and who to hand it off to. When a call goes beyond what it can resolve, it doesn't improvise: it routes it to whoever should handle it or takes down the details so someone can call back.

Natural voice and fluid conversations.
Available 24/7, with no queues or waiting.
Qualifies leads and books appointments.
Captures key information and logs it.
Integrates with your CRM and your tools.

How it works, step by step

Behind that natural feel is an orderly process. The assistant doesn't just talk: it follows a flexible script that you define, one that respects your business's tone and rules.

Listens and understands. It transcribes what the caller says and grasps the actual intent, not just isolated words.
Answers with judgment. It replies to frequently asked questions with the information you've given it about your business: hours, services, indicative prices, location.
Qualifies. It asks the key questions to find out what each person needs and whether it fits what you offer.
Acts. It books an appointment, takes down contact details or routes the call to the right department.
Leaves a trail. It logs a summary of the conversation in your CRM, so follow-up doesn't depend on anyone's memory.

For sensitive actions, the person is in charge, not the machine. The assistant proposes and prepares (an appointment, a quote, a detail that changes a record), but decisions that commit your business go through human approval. It's a copilot, not an autopilot.

An example to make it concrete

Imagine a dental clinic that gets a lot of calls throughout the day. Most are similar: hours, whether they work with a given insurer, how much a cleaning costs, whether there's an opening this week. A phone assistant can handle all of them at once, resolve those repeated questions on the spot and book anyone who wants to schedule a visit directly. Only the inquiries that truly need someone from the team (an emergency, a complex treatment) reach the front desk, already with the context gathered. The phone stops being a constant interruption and becomes a filter that works in your favor.

This is a hypothetical example, but the logic applies to almost any business with call volume: an advisory firm, a repair shop, a real estate agency, a store. In all of them, a good part of what comes in by phone is repetitive and perfectly automatable without losing that personal touch.

With control and data in the EU

Automating the phone doesn't mean losing control of what's said on your behalf. Every conversation is logged and can be reviewed, so you can always check what was answered and fine-tune the script. Data is handled within the European Union, and the assistant only works with the information you choose to give it. Everything is measurable: how many calls it handles, how many it resolves on its own, and how many it routes.

Your team, freed up

While the assistant filters and resolves the repetitive part, your team focuses on what actually adds value: closing deals, advising, taking care of the customer. AI doesn't replace your people; it takes off their plate the work no one wants to do. And when a call needs a person's touch, your team handles it fresh and with the context already prepared, instead of worn out after twenty identical inquiries.

More details at AI Agents & Assistants.

AIGiner Labs, our creative division, explained in depth: what it produces, how, and who owns the rights

Thu, 21 May 2026 00:00:00 GMT

We're introducing AIGiner Labs, the company's creative division, in more detail. Just like Solutions, it was born with AIGiner from day one, not afterward: if Solutions handles AI and automation for your business's processes, Labs brings that same technology to the creative side: audiovisual production, marketing campaigns and brand output. It's the other side of the same idea, not a later addition: that a small company can do things that used to be within reach only of large ones, without having to build an entire department to get there.

This isn't a last-minute idea. We spotted the same gap from both sides from the start: when talking automation with SMEs, many raise the same issue, that the business runs fine on the inside but the brand doesn't hold up on the outside. Websites that don't communicate, videos that never get filmed because the budget is scary, social media that stays half-finished for lack of time. Labs exists to fill that gap, with the same way of working that already defines us: close, honest and deliberate.

Big-brand production, without the big-brand cost

For years, making a good video or a strong campaign required shoots, crews, actors and budgets within reach of very few. AI changes that equation: high-level pieces can now be produced in a fraction of the time and cost, without giving up quality or brand control.

The important change isn't just the price, it's the pace. When production stops costing weeks, you can test, measure and adjust without betting everything on one perfect piece. An ad that doesn't work gets rewritten and regenerated the same day. A campaign adapts to a different audience or language without starting from zero. That turns creative work into something you can also iterate on, just like we do with automation.

What we do at Labs

Virtual avatars and presenters for your brand, recording whatever you need whenever you need it.
Influencers and digital characters with their own consistent identity.
AI-generated advertising creatives and ads.
Video, interviews and audiovisual production ready to publish.
Campaigns with content creators.
Recurring content for social media, so you never draw a blank week after week.
Creative websites with their own identity, not generic templates.

How we work: fast, but deliberate

Speed and control aren't at odds, and that nuance matters most to us. At Labs, AI accelerates the heavy lifting of production, but creative direction remains human. Nothing goes out without a person reviewing it and without your final approval. It's the same copilot, not autopilot, principle we apply to everything we do: the machine proposes and produces, the judgment and the final word are yours.

Briefing and brand direction: we define tone, message and style before touching anything.
Format or character design: we decide what type of piece tells your story best.
AI generation: we produce the creatives from that script.
Review with you: we adjust until the piece feels like your brand, not a machine.
Delivery ready to publish, in days rather than months.

An example to make it concrete

Imagine a small advisory firm that wants to explain its services on video, but never takes the step: it has no one comfortable in front of a camera and no budget for a shoot. With Labs, it could have its own virtual spokesperson presenting every service in short pieces for its website and social media. If it changes a rate or launches something new next month, there's no need to reshoot: the script gets adjusted and the new version is generated the same day. And if it wants to reach clients in another language, the same piece relaunches without starting from zero. This is a hypothetical example, but it reflects well the kind of problem Labs solves.

We learn from every project

Labs doesn't work piece by piece like someone who always starts from a blank page. Every project leaves us with a design system and a way of producing that makes the next one better and faster: we adjust color, typography, photography and structure to each brand starting from a solid, proven base. So what we learn from one project translates into the next client receiving more, sooner and at a higher quality.

The goal is for an SME to communicate like a big brand: with polished, consistent pieces produced in days, not months. The same technology as Solutions, applied to telling your story, and always with the same honesty: we tell you what can be done well, what can't, and why. No smoke-and-mirrors promises or inflated metrics.

Discover what we do at AIGiner Labs.

From script to video in days: how we produce with no studio, no shoot and no diaries to juggle

Sat, 16 May 2026 00:00:00 GMT

The question we get asked the most at Labs is: "can you really have my video ready this week?". The answer, almost always, is yes. And it's not because we rush or lower the bar, but because of how the process is set up: by separating the brand's face from the physical act of filming, much of the logistics that never shows up on screen disappears. What doesn't change is what truly matters: that the piece feels like yours.

This fits how we understand production at AIGiner: AI accelerates the repetitive part, but creative decisions still pass through a person. Copilot, not autopilot. We bring the same principle we apply in our business solutions here, to telling your story.

Where the time comes from

A corporate video isn't expensive just because of the shoot: it's expensive because of everything around it. Every script change means booking the spokesperson again, redoing makeup, lighting and sound, and adding another editing round. When the brand's face no longer depends on the physical act of filming, changing the message stops being a production problem and becomes a simple editorial decision.

A face of your own for your brand

We create virtual avatars and spokespeople who speak for your brand on your website, in ads and on social media. No photo shoots and no reshoots every time you change a line. An avatar that's 100% yours and records whatever you need, whenever you need it. It can be a character designed from scratch that embodies your company's tone, or a presenter format that gives continuity to all your pieces so that, wherever you see them, they're recognizable as yours.

The underlying advantage is consistency. When the same face always speaks, with the same voice and the same style, your brand gains memorability: people start associating that face with what you do, the same way it happens with a good logo or a recognizable typeface.

The flow: fast, but deliberate

Briefing and brand direction: we define tone, message and style before touching anything.
Character design or format selection: we create the avatar or choose the one that fits best.
Script and AI generation of the pieces: we turn your ideas into concrete scenes.
Review with you and adjustments: we iterate until it sounds and looks like your brand.
Delivery ready to publish, in days: with the formats and aspect ratios you need.

Speed and control aren't at odds. At every step, you decide: the tone, the message, what goes in and what doesn't. AI accelerates production; creative direction remains human, because that's what makes a piece feel like your brand and not a machine's. A video that impresses in the meeting but doesn't sound like you is worthless, and that's exactly what we avoid by reviewing every version with you.

An example to make it clear

Imagine a training academy that wants to present its courses for the term. With its own avatar it can produce a short welcome piece for the website, three brief videos (one per course) explaining what students will learn, and versions of those same videos in another language to reach new audiences. All with the same face and the same tone, produced in the same week. And if a date or price changes the following month, the script gets updated and the affected piece regenerated, with no need to set up another shoot. This is a hypothetical example, but it reflects well the kind of campaigns that are within reach of a small company today.

Multilingual, with no reshoots

Once the avatar is created, launching the same piece in another language or changing the script is a matter of hours, not another shoot. That opens the door to testing two versions of a message to see which works better, adapting the pitch for different audiences, or keeping content always up to date without the cost spiraling.

And as with everything we do, the final word is yours: nothing gets published without your approval. Technology brings the speed; the judgment, the voice and the responsibility for what goes out into the world remain with people. That's how Labs works: fast production, a polished result, and you in charge from start to finish.

See examples and services at AIGiner Labs.

Custom automations: from the process someone does by hand to the flow that runs on its own around the clock

Wed, 13 May 2026 00:00:00 GMT

We're reinforcing our process automation service: we connect the tools you already use and build workflows that run on their own. Follow-ups, reports, email sorting, data syncing between systems… repetitive work stops eating into your team's hours. This isn't about replacing the way you work, it's about taking off their hands the tasks that always get done the same way, with no judgment or room for decisions, and that still eat up attention every day.

The invisible work that holds you back

Every company carries around dozens of microtasks that nobody notices but that add up to hours every week: copying data from one tool to another, sending the same email as always, putting together Monday's report. Each one seems small; together, they're a full employee dedicated to copying and pasting.

The problem isn't just the time. It's that manual work is fragile: a follow-up gets forgotten, a figure gets typed wrong, an important email goes unanswered because it arrived at a bad moment. When a process depends on a person remembering to do it, sooner or later it fails. And it usually fails exactly when you're most stretched thin.

Those tasks are the first candidates for automation. They don't require creativity or judgment, just consistency, and that's exactly what a machine does best: repeating the same step, without getting tired, without getting distracted, and at the same time every day.

How we identify what to automate

Before touching anything, we listen. We sit down with you to look at how you actually work and look for tasks that meet three conditions: they happen frequently, they follow clear rules and they're currently done by hand. That's automation's sweet spot, where the savings are highest and the risk is minimal.

Frequency: something that happens daily or several times a week, not once a year.
Clear rules: if you can explain the process with an "if this happens, do that", it can be automated.
Little human judgment: the less subjective judgment required, the cleaner the workflow turns out.
Data that already exists: we work with the information you already have in your tools, without asking you to switch systems.

Whatever doesn't meet those conditions stays in your team's hands, which is where it belongs. Automating isn't about putting a machine into everything, it's about choosing carefully where it adds value.

Built for you, not from a template

Every automation is designed around your actual process, tested in a controlled environment and monitored once it's live. We don't sell generic templates: we start from how you work today and leave it running reliably, with alerts if something fails.

The difference between a template automation and a custom one shows up over time. The generic one works until your case strays slightly from the mold; then it breaks or forces you to change to fit it. The one built around your process adapts to your exceptions, your field names and your business rules, the ones only you know because you've spent years in your field.

How it works, step by step

We work in short phases so you see results early, with checkpoints along the way. We don't disappear for a month and come back with something already closed: we move forward with you watching.

We map the process: we document how it's done today, step by step, and where time gets lost.
We design the flow: we define what triggers the automation, what it does at each step and what tools it connects.
We connect your tools: we link your email, your CRM, your spreadsheets or your invoicing through their official integrations.
We test in a controlled environment: we run it with test data until it behaves correctly in both normal and edge cases.
We launch with monitoring: the flow goes live with active alerts, so if something fails you find out right away, not weeks later.

And we always keep the same principle that guides everything we do: the machine is a copilot, not an autopilot. For sensitive actions (sending something to a client, moving money, deleting records) the flow can pause to wait for human approval. You decide what happens on its own and what passes through your hands before it executes.

An example to make it concrete

Imagine an accounting firm that receives dozens of client invoices by email every month. Today, someone downloads them one by one, renames them, saves them in the client's folder and enters the data into a spreadsheet. It's slow, tedious work, and easy to get wrong.

With a custom flow, that same process happens on its own: when an email with an invoice attached arrives, the system detects it, extracts the key data, files it in the right folder and updates the spreadsheet. If it finds something questionable (an amount that doesn't add up, a client it doesn't recognize), instead of pressing on blindly, it alerts a person to review it. The team goes from typing to supervising, and only steps in when it's truly needed.

This is a hypothetical example, but the pattern repeats in almost any business: receive, sort, record and alert. The data and the tools change; the underlying logic is the same.

Reliable, measurable and with your data safe

An automation is only useful if you can trust it. That's why every flow is monitored and leaves a record of what it does: what ran, when and with what result. If something goes wrong, there's a trail that lets you understand what happened and fix it, instead of guessing.

That same record gives you something manual work rarely offers: visibility. You can measure how many times a process ran, how much time it saves and where it gets stuck. Everything is measurable, and what gets measured can be improved. We also put privacy first: your data is handled within the European Union and only moves between the tools you authorize.

Your team, freed up

While the flow handles the repetitive part, your team gets back hours for what truly adds value: thinking, deciding, taking good care of each customer. Automation doesn't lay anyone off; it gives your people back the time that today goes into copying and pasting. It's the same philosophy we apply to everything we build: technology does the heavy lifting and people do the work that matters.

Tell us which process steals the most time from you at Process Automation.

Website and video as a single piece: the method AIGiner Labs uses to put a whole brand on the street

Sat, 09 May 2026 00:00:00 GMT

At Labs we start from a simple idea: a brand isn't a logo, a website and a video separately; it's a single piece viewed from three angles. When those three angles are designed together, everything fits. When they're done separately and in a different order, it almost always clashes: the website says one thing, the video says another, and the logo looks like it belongs to a third project.

This article describes how we work, not a specific project. It's the method, told in general terms, so you know what to expect if you ask us for a creative website, a video, or both together.

The problem with producing in pieces

The common pattern in many projects is to chain suppliers together. One does the identity, another builds the website, and a third is brought in for a video once there's barely any budget left. Each one interprets the brand their own way. The technical result can be correct, but the whole thing feels stitched together: colors that aren't quite the same, a typeface in the video that doesn't appear on the website, a photography tone that doesn't match the rest.

That patchwork has a real cost. Every change requires touching three places, every review opens three different conversations, and the brand comes across as less solid than it actually is. We prefer to avoid that from the start.

Designing the language before the pieces

Before opening a single screen or filming a single shot, we define the brand's common language. It's not a long document or a theory: it's concrete decisions that then govern everything else.

Color: a short palette with clear hierarchy. What leads, what supports and what's reserved for accents.
Typography: one family for headlines and another for body text, with size and rhythm rules that work equally well on a website and in a video's on-screen text.
Photography and motion: the type of image, the light, the framing and the editing pace. If the website breathes calm, the video can't be cut at a frantic pace.
Voice: how we speak in a headline, in a button and in a voiceover. The same person behind every sentence.

With that language set, the website and the video stop being two projects and become two outputs of the same original. The headline that opens the home page is the same one that opens the video. The blue of the button is the blue of the on-screen text. The photo you see while scrolling has the same light as the opening shot.

One project gives birth to a system

This is the part we like most. When you design the language and then build the website and the video on top of it, you don't end up with just two deliverables: you end up with a design system. That is, a set of already-solved sections, components and templates you can reuse.

A system isn't a cloned website. It's more like a smart mold: the sections almost any brand needs (a strong hero, a services area, proof and trust, a closing call to action) are already thought through, tested and ready. What changes from one brand to another are the variables.

Color and typography: adjusted to each brand's identity without redoing the structure.
Photography and video: the same skeleton supports a warm, human tone or a sober, technical one.
Sections: turned on, hidden or reordered based on what each business needs to say.
Content and voice: the copy is rewritten entirely, but built on a structure we already know works.

The practical effect is twofold. On one hand, we produce faster: we don't start from a blank page every time, but from mature pieces that just need dressing up. On the other, we raise the quality floor: since the sections are already polished, no brand starts from something mediocre. Speed doesn't come at the cost of sloppiness.

Fast doesn't mean identical

It's worth saying this plainly, without hype: reusing a system does not mean every website looks the same. The structure is inherited; the skin is unique. Two brands can share the same section skeleton and look completely different because color, typography, photography, pace and voice all change. Imagine a bright, delicate cosmetics brand and a raw, direct-energy gym: the same mold produces two results no one would call related.

And when a brand asks for something the system doesn't cover, it gets custom-designed. The system is a starting point that saves repetitive work, not a straitjacket. The good thing about having it is that creative effort concentrates where it actually matters: on what makes each brand unique, not on solving a footer for the umpteenth time.

What you walk away with

If you work with Labs, you don't walk away with three loose files that someone will have to stitch together later. You walk away with a brand that's consistent across website and video, speaking the same language, and a foundation ready to grow: tomorrow you need a new section, a campaign or one more video, and there's nothing to reinvent, because the language is already defined and the system already exists.

Do you have a brand that deserves to look like a single piece? Tell us what you want to build at Contact or discover how we work at AIGiner Labs.

Free AI audit: find out what you can automate and how many hours a month it gives you back

Fri, 24 Apr 2026 00:00:00 GMT

We're launching the free AI audit: a no-strings-attached analysis of your business to find where artificial intelligence and automation can generate the most savings in time and money. It's not a sales demo or empty talk: it's an honest diagnosis of how you work today and which parts can be lightened without breaking anything that already works.

Starting is the hardest part

The question usually isn't "do I want to use AI?", but "where do I start?". It's easy to get lost among tools, demos and promises that claim to solve everything and end up just adding another subscription nobody uses. The audit is designed exactly for that: to bring order and give you a clear starting point, based on your actual business and not on whatever's trendy this season.

In most small and medium businesses, the problem isn't a lack of technology, it's a lack of judgment to choose. There are too many options and too little time to test them. The usual result is paralysis: it gets left for "whenever there's a gap" and that gap never arrives. An external, orderly diagnosis with no sales pressure breaks that block because it turns a vague intention into a concrete list of steps.

Why we do it for free

Because we believe no one should have to pay to find out whether AI is useful to them. We'd rather you see the value first and then decide, with the information in front of you, whether to move forward with us or on your own. A well-done audit is useful in itself: even if you don't end up working with AIGiner afterward, you walk away with a map you can execute with whoever you choose. Our philosophy is simple: free before paid, and honesty before hype.

It's also the best way to start a working relationship right: with no surprises. If, when analyzing your processes, we see that AI adds little value in your case, we'll tell you with the same clarity. Recommending automation for something that doesn't need it would betray the reason we exist.

What it includes

A review of your current processes and tools: how work comes in, who touches it and where it gets stuck.
Identification of concrete automation opportunities, prioritized by effort and impact.
A report with a phased plan and a realistic estimate of time saved.
No commitment and under a week, with a closing conversation to answer questions.

How it works, step by step

The process is lightweight by design: we don't want to steal half your day or ask you to document your entire operation before starting. We run it in four steps.

Initial conversation (30-45 min): you tell us what your company does and which tasks eat up your day. No preparation needed.
Internal analysis: we review the flows you've described, look for bottlenecks and work out what can be solved with automation, with an AI agent, or simply by reordering the process.
A prioritized report: we hand you a short, readable document, not a technical brick, with opportunities ranked by what pays off most for the least effort.
A closing session: we go through the report together, answer questions and you decide the next step. No pressure.

You're in charge the whole time. We work with the idea of a copilot, not autopilot: sensitive decisions pass through a person, everything gets logged and your data is handled within the European Union. The audit doesn't touch anything in your operation; it only looks, organizes and proposes.

An example to make it concrete

Imagine a small online store that gets dozens of client emails every month asking about the same thing: an order's status, an exchange or a return, almost always with incomplete details and no order number. Someone on the team spends hours reading them, chasing what's missing and sorting them by hand before the real work even starts. In an audit, that would be a clear candidate: an assistant that acknowledges receipt, checks whether the email has all the necessary information and, if not, politely asks for what's missing, leaving the case ready for a person to review and approve.

It doesn't replace anyone: it removes the mechanical, repetitive part so the team can spend its time on judgment, which is what adds value. That's exactly the kind of opportunity a diagnosis brings to light and that, in the day to day, almost never gets noticed because "it's always been done this way". This is an illustrative, hypothetical example, but it reflects well the kind of tasks we look for.

What you walk away with

By the end you'll have a map: what to automate first, what savings to expect and what to leave for later. You'll also know what's not worth touching yet, which is often the most valuable conclusion. Whether you use it with us or on your own, it's yours to keep. No fine print and no obligation to hire anything.

And if you decide to move forward, that report is the perfect foundation for the next step, made with a clear head: for example, bringing in our AI agent products starting with just the process that hurts you the most, instead of trying to change everything at once. Small, measurable, and with human approvals where they matter.

Request it at Free Audit.

What "artificial intelligence with a human soul" means, and why it is not a slogan

Sat, 18 Apr 2026 00:00:00 GMT

"Artificial intelligence with a human soul" isn't a slogan we put up to sound good. It's the way we decided to build everything we do, and it shows in product decisions, not just on the home page. When a phrase is genuine, you can trace it down to the code, to the permissions and to what the tool lets you do or not do. Here's what's underneath.

AI in the service of people

Artificial intelligence allows for very different uses, and not all of them pursue the same thing. We build so that it takes off people's hands the work nobody wants to do, and so they can spend their time on what actually matters.

The difference isn't a nuance, because it shapes what gets built and what doesn't. A system designed to replace people acts on its own, hides what it does and measures its success in headcount saved. One designed to free up time shows what it proposes, asks permission before touching anything sensitive and measures its success in hours recovered. We build the second.

That's why our products are copilots, not autopilots. Our agents don't act behind your back: important decisions pass through a person and get logged. AI proposes and executes the repetitive part; judgment remains human. Work is also organized by department, with a coordinating agent directing the specialists, the same way you'd coordinate a team. You set the direction; they handle the heavy lifting.

How that translates into the product

A principle that doesn't change how the tool actually works isn't worth much. These are the concrete mechanisms through which "human soul" stops being a phrase and becomes system behavior:

Human approvals on the actions that matter: sending an email to a client, changing a sensitive piece of data or publishing something outward never happens without a person saying yes.
Audit trail: every action is logged (who, what and when), so you can always reconstruct what happened and why.
Data hosted in the European Union, with privacy as a starting point rather than a last-minute add-on.
Everything measurable: if we promise time savings or less friction, it has to be verifiable with real numbers, not a feeling.

Notice that none of these points is decoration. Each one takes power away from automation and hands it back to the person. That is, in practice, the "human" part of it.

An example to make it concrete

Imagine a small optician's shop that gets dozens of client emails every morning: questions about whether their glasses are ready, appointment requests for eye exams, inquiries about warranties and quotes. Without help, someone on the team spends the first hour reading, sorting and writing almost identical replies over and over.

With a properly understood copilot, the agent reads those emails, groups them by type, prepares draft replies and flags the three cases that truly need a human decision. But it doesn't send anything on its own: it leaves the drafts ready for a person to review, adjust the tone and approve. The repetitive part disappears; the judgment (what gets said to each client) stays where it belongs. And if someone asks tomorrow why something was answered, the log tells the story. This is a hypothetical example, but it describes exactly how we think through every flow.

Closeness, not jargon

The "human soul" isn't only in how the software behaves, but also in how we treat the people who use it. We'd rather explain things in plain language, and it shows in how we treat people:

We speak plainly: no jargon to impress.
We give options and ask before making a mess of things.
We stick around, we don't just hand over a tool and disappear.
We measure what we promise.

Speaking plainly doesn't mean oversimplifying or hiding from you what the tool does underneath. Quite the opposite: we'd rather explain it to you once, simply, than have you trust us blindly. A team that understands what it uses, uses it better, controls it and trusts it. And trust, in something that touches your customers' data, isn't an extra: it's the foundation.

We believe the best technology is the kind you barely notice: the kind that makes your day easier without you having to think about it. If by the end of the month your team is working with less friction and more comfort, we've done our job well. That is, for us, what it means to put a human soul into AI: not a machine that decides for you, but one that gives you back time and leaves decisions where they should always be, in people's hands.

Learn our story at About Us.

AIGiner Solutions: AI, automation and integration for the SMEs that have no technical team in-house

Fri, 10 Apr 2026 00:00:00 GMT

We're consolidating AIGiner Solutions, our AI and automation division. The proposition is clear: any company can adopt artificial intelligence even without a technical team, without the project ending up as a pretty demo nobody uses.

Most SMEs we talk to don't struggle from a lack of ideas, but from a lack of a bridge. They've seen what AI can do, they sense it would help them, but between that instinct and having it running in their company lies a gap of tools, integrations and technical decisions that no one in-house has time for. Solutions exists to cross that bridge with you, and leave it crossed.

We don't sell demos, we build systems

The AI graveyard is full of proofs of concept that impressed everyone in a meeting and were never opened again. We work the other way around: we start from a real problem in your business and we don't stop until the solution is integrated into your day to day and people actually use it.

The difference between a demo and a system is boring but decisive: the edge cases, the data that doesn't fit, the colleague opening it at eight in the morning in a rush. A demo falls apart at the first case that wasn't in the script; a system is designed for that case. That's why we measure a project's success by a single thing: that weeks later it's still in use, with no one having to remember how it worked.

Why SMEs get left out (and why they shouldn't)

Large companies have spent years investing in artificial intelligence with dedicated teams. Small and medium ones can rarely afford that: they have no technical department, no time to research tools, and no appetite for signing a long, expensive project whose return no one guarantees. The result is that they get left out of a technology that, applied well, is precisely the one that changes their day the most, because every hour saved weighs far more heavily in a small team.

Our way of closing that gap is to start small, at the point where it hurts. You don't need to transform the whole company to feel the difference: it's enough to take off a repetitive task that eats up hours every week and build on that first win. Trust is earned with something that works, not with a presentation.

How we work

Diagnosis of your processes: where time and money are being lost.
Strategy with measurable impact, not smoke and mirrors.
Integration into your current systems, without reinventing anything.
Support through deployment and training for your team.

Every phase delivers something tangible. From the diagnosis you get a clear map of opportunities ranked by impact; from the strategy, a plan stating what to do first and what to leave for later; from the integration, a solution connected to your data and the tools you already use; and from the support, a team that knows how to run it without depending on us for everything. The goal isn't for you to always need us, it's for you to walk away with autonomy.

An example to make it concrete

Imagine a real estate agency that spends half the morning sorting emails from interested buyers, finding the right listing and writing similar replies over and over. Instead of replacing anyone, we set up an assistant that reads every incoming email, links it to the client and the property, and prepares a draft reply with the information already looked up. The person reviews it, adjusts the tone if needed, and sends it. The machine does the tedious work; the decision and the relationship with the client remain human.

This example is hypothetical, but it reflects how we understand AI in everything we do, including the agent systems we build: copilot, not autopilot. Sensitive actions go through human approval, everything is logged in an audit trail, and data is handled within the European Union. It's not a legal footnote: it's the only way you can genuinely trust delegating something.

And all of it connected to your data, integrated into your processes and measurable from day one. Because an AI you can't measure is an AI you can't trust. If a few weeks later you can't say what's improved, we haven't finished our job.

Start with a free audit or write to us at Contact.

AIGiner launches in Barcelona: two divisions, one way of working and no promise we cannot keep

Wed, 01 Apr 2026 00:00:00 GMT

AIGiner launches, an artificial intelligence and automation agency based in Barcelona. We're built with freelancers, professionals and small and medium businesses in mind, ones that want to use AI for real and don't have an in-house technical team to build it for them. The underlying conviction is simple: artificial intelligence shouldn't be a privilege reserved for large corporations with a data department and an almost unlimited budget. It should be within reach of any business that wants to work better, regardless of size.

The gap between the hype and what actually gets used

Today artificial intelligence is talked about everywhere, but most real businesses still haven't seen how it changes their day to day. Between the promise and the practice there's a well-known gap: demos that impress in a meeting and end up in a drawer, reports with recommendations no one ever executes, pilots that stay pilots forever. AIGiner is born exactly in that gap, with the opposite idea: we don't sell proofs of concept or pretty reports, we build systems that get used every day and can be measured in time and money.

The problem is almost never the technology itself, but everything around it: not enough hands to configure it, not enough judgment to know what's worth it, and not enough trust to let a system touch processes that pay the bills. Many tools promise magic, ask for a card and leave the business alone in front of a dashboard nobody knows how to use. We prefer the opposite path: support, explain and demonstrate before asking for anything.

Two divisions, one idea

We're organized into two divisions that share technology and philosophy. Solutions brings artificial intelligence and automation to the processes that keep a business running day to day: custom AI agents, process automation, tool integration, chatbots, voice AI and a phone assistant that answers calls around the clock, plus data analysis, training so the team gets the most out of AI, AI search over the company's own documents, and consulting with an initial audit that's always free.

Labs brings that same technology to the creative side: creative websites with their own identity, video and interviews, brand avatars, virtual influencers with their own personality, campaigns with content creators, AI-generated ads and recurring content for social media. The idea is for a small company to communicate with the production values of a big brand, without the cost or timelines of a traditional shoot.

Different surfaces, the same philosophy: useful technology, applied and within reach of any business. No smoke and mirrors, no jargon, and results that can be measured.

How we work

The method doesn't change based on the project:

We always start with a free audit, no strings attached, to know from the data where AI genuinely saves time and money and where it's not worth touching anything.
Every project has a closed scope, with what's included and what isn't, before anything gets signed.
Prices are published on the website, always "starting from", with nothing hidden behind a sales call.
The work doesn't end at delivery: we continue with maintenance and support after launch.

We'd rather be a smaller company with clients who trust what we say than one that grows fast on promises we later have to walk back. If, when analyzing a specific process, we see that AI adds little value in that case, we say so with the same clarity as if it added a lot.

A European commitment

All infrastructure and data processing happens within European territory. Privacy is designed in from the start, not bolted on at the end, in compliance with GDPR, and our AI policy explains in detail which tools we use and how we use them, with no fine print.

Where to find us

The website is bilingual, in Spanish and English, with guides for 17 industries detailing concrete automation cases sector by sector, from finance to real estate. You can reach us by email, by WhatsApp, by filling out the contact form, or by requesting the free audit directly.

This is the starting point, not the destination. AIGiner launches today in Barcelona with a very concrete idea of where we're headed: bringing artificial intelligence within reach of those who never thought it was within theirs, calmly, deliberately and with no fine print. From here on, the plan is to keep growing in Barcelona and across Spain, one well-made project after another.

Meet the team and the story at About Us.