data.alive.family

The new era of the internet

For the first time, the internet is mostly not human. What does that mean for you?

53%

of all web traffic came from machines, not people.1

50%

of newly published online articles are primarily AI-generated.2

8%

of people click a link when Google shows an AI summary. Without one, 15 %. On the sources the summary cites: 1 %.3

When machines do the talking, the human becomes precious.

What is happening

Three ideas that explain the shift better than any forecast.

Abundance makes its opposite valuable

Ice was a luxury until freezers arrived. Then cold became ordinary and the rare thing was a glacier.

Content has become infinite. What is running short is trust, authenticity and lived experience. Anything a machine can produce in seconds stops being an argument.

A signal only counts if it costs something

A peacock’s tail is a burden. That is exactly why it is honest: only a healthy bird can afford to drag it around.

Biologists call this the handicap principle. A message that costs nothing says nothing. Showing up in person, filming on location, signing your name — all of it costs. That is what makes it credible.

The more that can be copied, the more the unique one is worth

A print of a painting hangs in a million living rooms. People still queue to stand in front of the original.

Walter Benjamin called it the aura: the here and now of a thing, its presence in a particular place at a particular time. Copies multiply. The original does not.

AI in the engine room. People at the front desk.

„The medium is the message.“
Marshall McLuhan

When content becomes infinite, scarcity shifts to trust, cost and originality.

Service 01

Getting AI projects done.

We take companies from the first idea to a system that runs. No pilot that quietly dies, no workshop that ends in a slide deck. We also tell you when AI is the wrong tool — which it often is.

01

Understand

We sit in on the actual work for a day. Not a questionnaire: the real process, with the shortcuts and the annoyances nobody writes down.

02

Test

One narrow case, built small, measured honestly. If it does not hold up, we say so and stop. That is cheaper for everyone than a year of enthusiasm.

03

Build

Into your accounts, on your access, with your data. Documented in a way your people can read.

04

Look after

Systems drift. Models change, interfaces move, processes grow. Somebody has to keep watching — either us or you, but somebody.

What we will tell you

  • When a spreadsheet would do the job better than a model.
  • When the process itself is the problem and no tool will fix it.
  • When the data you have is not good enough yet, and what it would take.
  • When the honest answer is: not worth it.

From 2 August 2026, EU rules require AI-generated content to be recognisable as such. We help you put that into practice in your own operation — see Transparency below.

Most AI projects fail on the process, not the technology, so we start with the process.

Service 03

Automating the work nobody should be doing.

Two ways in. Pick the one that fits how you want to work afterwards — that decision matters more than the choice of tool.

We run it

We build the process and operate it. You get the result, not the maintenance.

  • Runs in your accounts, never locked to ours
  • Monitoring and repair included
  • Monthly, cancellable, no lock-in

We teach it

We build the first one with your people watching, then hand over everything — the prompts, the tools, the reasoning.

  • Your team builds the next one alone
  • Prompts and configurations belong to you
  • We stay reachable, not necessary

Automate the cost, not the relationship.

Bill Gates put it roughly like this: automation applied to an efficient operation magnifies the efficiency; applied to an inefficient operation, it magnifies the inefficiency. Which is why we start with the process, not the tool.

„The hottest new programming language is English.“
Andrej Karpathy

Automating a broken process makes it break faster, so the process comes first.

For AI teams

Human footage for the age of machines.

Licensed video and audio produced by a film crew, with documented provenance, signed consent covering AI training, and cleared rights. Commissioned to your spec, or from unreleased archive.

Models trained on model output degrade

Shumailov et al. showed in Nature that generative models trained recursively on generated data lose the tails of the original distribution — the rare cases disappear first, and the output flattens toward the average. Real human material is not a nice-to-have. It is the correction.4

The stock is finite. The flow is not.

The archive of everything already written and filmed is being bought up. What nobody has finished scanning is the present: new places, new faces, work being done with hands, languages still being spoken.

Most of what people know was never written down

Michael Polanyi called it tacit knowledge: we can know more than we can tell. A cook adjusts by feel. A technician hears the fault before the meter shows it. That knowledge exists only where it is performed — which is to say, on camera or nowhere.

The market already pays for this

Reddit licenses its conversations to Google and OpenAI. Bloomberg reported in January 2025 that AI companies were paying one to four dollars per minute for unreleased video, with premiums for 4K, drone footage and 3D animation.6

A — Commissioned production

New material, shot to your specification by a film crew.

  • Locations, situations, trades, hands at work
  • Language and dialect, including regional variants
  • Aerial work by licensed drone pilots
  • Multi-camera, 4K and above, raw files on request

B — Archive licensing

Unreleased material from the network and its partners, prepared and cleared.

  • Catalogued, described and technically checked
  • Rights cleared for music, locations and brands in frame
  • Consent confirmed or re-obtained where needed
  • Delivered with the same documentation as commissioned work

What comes with every delivery

  • Provenance: recordings signed with Content Credentials (C2PA) wherever the equipment supports it.
  • A complete record of place, date, crew and every processing step.
  • Signed releases from everyone appearing, with an explicit clause covering AI training.
  • Cleared rights for music, locations and visible brands.

Where we are careful: C2PA proves provenance, not truth. It tells you where a file came from and what was done to it — it cannot tell you whether what was filmed was staged. And many platforms still strip the metadata on upload, so the chain can break outside our hands. We document anyway, because a broken chain you can see beats no chain at all.

„We can know more than we can tell.“
Michael Polanyi

AI needs material it cannot generate itself, with provenance and consent that hold up.

Proof of concept

What is already running.

Production & content

Documented work by the TeamAlive network. We have been producing exactly the kind of material that is becoming scarce, for years, for reasons that had nothing to do with AI.

Alive Festspiele

A cultural festival on Lake Constance, put together in 2020 — the year festivals were being cancelled everywhere else.

Alive Wohnzimmer Festival

A livestream festival with artists across several continents. The stages were the social media channels of regional businesses.

Anything To Say

A production for World Press Freedom Day.

Alive Time Capsule

A format that records the stories of particular places for the future.

Short film production

Produced in-house, selected at international festivals.

We did not start filming because AI needed data. We were already there.

Software & automation

Case studies without names. Everything here was built for a business inside the network and used daily before it was offered to anyone else.

Staff portal, hospitality business on the lake

1
Event staffing ran on group chats and a wall planner. Who was working when was a weekly argument.
2
One portal for event registration and shift organisation, built around how the team already worked.
3
[Placeholder: hours saved per week — to be filled from actual figures]

Dashboards, hospitality

1
Numbers lived in four systems. Nobody looked at them until the end of the month.
2
One screen, the figures that actually drive decisions, updated daily.
3
[Placeholder: concrete outcome — to be filled]

Shift team communication

1
Important messages disappeared in a chat group nobody could search.
2
A channel built for shift work: reaches people, stays findable.
3
[Placeholder: concrete outcome — to be filled]

HR process

1
[Placeholder: starting point — to be filled]
2
[Placeholder: solution — to be filled]
3
[Placeholder: outcome — to be filled]

Booking platform, event technology supplier

1
Enquiries arrived by phone and mail and were transcribed by hand into a calendar.
2
A booking platform with an automated daily marketing report on top.
3
[Placeholder: concrete outcome — to be filled]

Everything was tested in our own businesses first.

Coverage and partners

[Placeholder: logos of press coverage and partners — only with written clearance from each party]

The network has been producing human content and running its own software for years.

Transparency

Saying what is machine-made.

What the law asks for

Since 2 August 2026, Article 50 of the EU AI Act requires AI-generated content to be marked in a machine-readable way and made recognisable to people. The rules distinguish between content that is fully generated or substantially altered by AI and content where AI only assisted with ordinary editing — the second case is exempt. Systems already on the market before that date have until December 2026.7

This page, specifically

With AI assistance

  • Drafting and structuring of these texts, edited and approved by people
  • Translation into the four languages, reviewed by native speakers
  • Code and build tooling

Without AI

  • Every photograph and every frame of film — real places, real people, real work
  • Every figure quoted, each with its source
  • The positions taken here

We help you work out what this means for your own content and how to label it without turning every page into a legal notice. That is part of Service 01 and 03.

We are not lawyers and this is not legal advice. For binding questions we work with lawyers who are.

From August 2026 AI-generated content must be recognisable, and we apply that to ourselves first.

How we work

The boring part, said plainly.

A network, not an agency

data.alive.family is the AI, data and automation arm of the TeamAlive network: creatives, technicians, filmmakers, drone pilots, event people and business owners across the border region. Each project gets the people it actually needs.

Practitioners, not advisers

The people here run restaurants, event technology, software and film production. The tools we recommend are the tools we use on our own Mondays.

Data stays in the EU

GDPR-compliant by default, hosting in the EU, and a clear answer to where every piece of data sits. If a project needs something outside the EU, you hear it before it happens, not after.

Rooted here, working anywhere

Based in the Lake Constance region, working across Austria, Germany, Switzerland and beyond. Being from somewhere is an advantage when the job is to film it.

[Placeholder: client voices — published only with written consent. We would rather show nothing than invent something.]

A network of practitioners who use the tools they recommend, with data kept in the EU.

Questions

What people ask first.

What is the difference between AI-generated and AI-assisted?

AI-generated means the machine produced the content. AI-assisted means a person made it and the machine helped — correcting, shortening, suggesting. Under Article 50 of the EU AI Act, the first case must be marked. The second is exempt as long as the assistance does not substantially change the content or its meaning.

Does my business have to label AI content?

If you publish content that was generated or substantially altered by AI, yes, since 2 August 2026. If AI only helped you edit something you wrote, no. The grey zone in between is where most businesses actually sit, and it is worth going through your own cases once rather than guessing.

What does it cost to start automating?

We do not publish prices, because the honest answer depends entirely on the process. What we can say: we start with one narrow case you can measure, not a platform. If that case does not pay for itself, there is no reason to continue, and we will say so.

Can we keep developing the system ourselves afterwards?

That is one of the two ways we work, and the one we recommend when you have people who enjoy this. You get the prompts, the configurations and the reasoning behind them. It runs in your accounts. We stay reachable without being necessary.

Why does AI need human data at all?

Because models trained on model output degrade. A Nature study by Shumailov and colleagues showed that recursive training on generated data makes the rare cases disappear first and the output drift toward the average. New human material is the correction — and unlike the archive of the past, it is not finite.

How do you prove that footage is human?

Three layers. Content Credentials (C2PA) signed at the camera where the equipment supports it. A documented record of place, date, crew and every processing step. Signed releases from everyone appearing, with an explicit AI-training clause. None of it proves what happened in front of the lens — it proves where the file came from and who agreed to what.

Do you make AI avatars or AI video?

No. We use AI for processes — the work behind the scenes. We do not use it to replace the people in front of the camera. That is the whole position, and it is also why Service 02 exists.

Where is the data stored?

In the EU, by default, and we tell you which provider. If a specific project needs a service outside the EU, you hear about it while the decision is still open.

Get in touch

Tell us about your process.

Hegel wrote that the owl of Minerva takes flight only at dusk — understanding arrives after the day is over. That is a fair description of how these systems work: they learn the world in hindsight. Living in it happens earlier, and that part is still yours.

„The future is already here — it’s just not very evenly distributed.“
William Gibson

No qualification form, no funnel. Describe the thing that keeps costing you a morning every week, and we will tell you honestly whether we can help.

We use your message to answer it. Nothing else, no newsletter, no transfer to anyone.