AI visibility for industrial companies
In industrial business, sourcing rarely starts with a phone call. A buyer or design engineer asks: "Which manufacturer produces sheet metal parts up to 8 mm in small batches?" – and gets a handful of names. If you are not among them, you never reach the enquiry stage.
The companies that get named are those whose processes, materials, tolerances and batch sizes appear as text on the website. If your technical data only lives in a PDF catalogue, you are effectively absent for a language model.
On top of that, a problem that hits mid-sized manufacturers hardest: many have sold through trade fairs, referrals and existing customers for decades. The website is a business card. For an AI that is not enough to match the company to a specific need.
Why does an AI-assisted buyer find our competitor and not us?
Because the competitor's technical data sits as text on the page, while at most industrial companies it sits inside a PDF. A language model reads processes, materials, tolerances, batch sizes and certifications only when they appear as running text or a table in the page itself. It also needs the link between process and application: not just "five-axis milling", but what it is used for and in which dimensions.
What we measure in industry
These figures come from our own measurement series – not from a study, not from an estimate.
Mention rate of the median company: how often it appears in an answer at all.
Between the weakest and the strongest company measured. The gap is the room to move.
AI answers evaluated in this sector.
Live measurement questions running in this sector.
Our own measurement series, data through 13.09.2026. Four AI systems (ChatGPT, Gemini, Perplexity, Grok), measured weekly. No company names, no estimates – where the data is too thin, no figure is shown.
How customers actually ask
Question types from our own measurement series, reworded generically – company, place and product names removed.
- „Which manufacturer produces sheet metal parts to drawing in small batches?"
- „Who can weld stainless steel and deliver with certification?"
- „Which company builds special machinery for food processing?"
- „Who produces turned parts in low volumes with short lead times?"
- „Which supplier can laser cut up to 20 mm?"
- „Who assembles sub-assemblies and ships directly to the customer?"
- „Which company offers contract manufacturing with in-house design?"
- „Who supplies spare parts for older machines from a sample?"
- „Which manufacturer has experience with cleanroom requirements?"
- „Who can build prototypes and later move to series production?"
- „Which company manufactures to ISO 9001 with full documentation?"
What is usually missing
- Technical data locked in PDFs
Catalogues and data sheets are made for people. AI systems read them poorly or not at all. Materials, dimensions, tolerances and processes belong in the page text – then they can be cited.
- No statement on batch size and capacity
Buyers almost always ask about quantity and lead time. If nowhere on the site says whether you do one-offs, small batches or volume, you drop out of exactly those questions.
- Certificates as logos only
ISO 9001, IATF, welding approvals: as a footer image they are invisible. Named, with their scope, they become a selection criterion a model can use.
- No link between process and application
A list of machines says nothing about the problem solved. Companies that connect the two – "we use this to produce housings for drive technology" – get named in application questions.
How we work with you
- Where does your company stand?
We put the questions your buyers ask to four AI systems – without naming you. You see which competitors get named instead.
- Building blocks for your site
Making technical data machine-readable, structured data, llms.txt. The fastest route when the content already exists.
- Rework your existing site
We bring the manufacturing depth out of your PDFs into readable text, without replacing your documents.
- A new website
If the site dates from a time when Google was the only route, we rebuild it.
- Ongoing support
Monthly measurement and upkeep. New processes, machines and materials belong on the site promptly, or the profile goes stale.
Questions
- Our customers come from trade fairs and referrals. Is that not enough?
- It was, for a long time. But the people on the other side are changing: younger buyers research digitally first and increasingly ask AI systems. If you do not appear there, you do not make the enquiry list – however good the work has been for forty years.
- We are not allowed to name our customers. Does this still work?
- Yes. What matters to an AI system is the type of project, not the client name: part, material, process, quantity, particular challenge. Such descriptions are citable and breach no confidentiality.
- Do we have to publish our prices?
- No. Prices play almost no role in how a model selects – processes, capacity and evidence do.
- What does it cost?
- Scope and starting point differ a lot, so we discuss the price in a first call. The GEO check beforehand is free.
Regions where this sector is strong
Other sectors
Not quite your fit? The questions differ by sector – the method does not.
Where do you stand in industry?
The GEO check takes seconds and costs nothing. For the full picture we measure four AI systems against the questions above.