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Manufacturing

Each shop in the group quotes alone, from its own past jobs

How do we quote faster across the machine shops we have bought, when each one keeps its own job history?

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Figures and rules on this page apply to

Europe

Working somewhere else? The shape of the problem usually travels. The deadlines do not.

What this looks like

A customer emails a drawing for a welded bracket. One shop's estimator prices it from scratch over two days. Another shop in the same group made almost the same part last spring. Nobody knew, because each shop's job history lives in its own system.

The numbers

Every figure here is someone else’s. Check them.

  • 17%share of small EU enterprises using any AI technology in 2025
  • 55%share of large EU enterprises using AI in 2025, more than three times the small-firm rate
  • 3.7mpeople employed by EU makers of fabricated metal products in 2023, the second-largest manufacturing employer
  • 2.2mmanufacturing enterprises in the EU in 2023, most of them small

Why it happens

It is not a people problem.

Every shop records its jobs correctly, in its own words. One calls it an article, another a drawing number, another a customer part. Materials, routings and hours are logged in different ways. So a past job that would answer today's quote is invisible from the shop next door.

Why your current software has not fixed it

Because it was never built to.

The usual fix is one ERP for the whole group. That takes years, and the owners of each shop chose to keep their own way of working. Meanwhile the next shop joins with a third system. Quoting stays local because the records are local.

Intelligence, plumbed in

A scanned drawing and a customer's email can be matched to a similar part made years ago at another site.

We build a layer that reads every shop's job history. Each new drawing then starts from the closest job the group has made. Underneath it: a connector, one agreed meaning per field, and a test set scored on your own records.

How we make AI survive real data
  • Connectors
  • A semantic layer
  • Evals you can check

However hard, whatever it is

Machine and sheet-metal shops are one example. Bring the quote that takes longest.

We wrote this about groups of job shops because each purchase adds records nobody else can read. The same gap exists in any group that grows by buying similar firms.

  1. 01

    We sit with you

    Days where the work happens, not a workshop in a meeting room. We watch the job get done and write down the shortcuts nobody wrote down.

  2. 02

    We read everything

    Your data, your rules, your vendors and their documentation, and the published research on your sector. We report what is actually in there.

  3. 03

    We break it to first principles

    Not which tool fixes this. What is actually causing it, taken apart until we reach the piece that cannot be divided further.

  4. 04

    Then we build

    Weeks, not quarters. By this point we are not guessing what to build, and guessing is the thing that makes projects long.

What we build

Specific enough to argue with.

Four mechanisms, not four features. Each one is a thing that happens on its own, every day, whether or not anyone remembers to run it.

  • Customer drawings and quote requests read on arrival, whatever format the customer used.

  • Similar past jobs found across every shop in the group, with real hours and material used.

  • A draft quote for the best-placed shop, for its estimator to check and send.

  • One view for group management of open quotes, win rates and spare capacity by shop.

How you would know it worked

Numbers in your own reporting, not ours.

  • Hours from a customer drawing arriving to a quote being sent.
  • Share of quotes that start from a matched past job instead of a blank sheet.
  • Number of jobs placed with a sister shop instead of turned down.

Straight answers

Where a model is involved, it is scored against your own records first. Accuracy per source, not one flattering average.

The questions this raises

  • Each of our companies runs its own business.

    They still do. The layer reads each shop's records and changes none of them. Each shop decides whether to use the draft.

  • Our estimators know things no system does.

    That is why they check every draft. The layer removes the searching and re-typing, not the judgement.

  • How soon would we see a difference?

    Usually within weeks, starting with the shops that receive the most drawings. Each newly bought shop can be connected the same way.

Also in manufacturing

The meaning is not in any schema

Two systems agree on the field and disagree on what it means.

The rule lives in a document, or in what one site has always called something, or in a habit nobody wrote down. Joining the data is the easy half; agreeing what it means is the half that is actually the work.

Consent rules, site vocabulary, what an hour counts as. Wherever two systems agree on a field and not on what it means.Describe the disagreement.

The group already knows the price. It just cannot find it.

We build a layer that reads every shop's job history. Each new drawing then starts from the closest job the group has made.

See everything we build
  • Software
  • Hardware
  • Ways of working
  • Whole ventures

Is this happening to you? Tell us the size of it.

Twenty minutes. We will tell you honestly whether the numbers justify doing anything about it.