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Practical AI for the factory

One KPI, one use case, a small pilot, and an honest answer.

AI only where it moves a number you care about, starting from the data you already have.

Why it matters

You do not need an AI strategy deck. You need to know whether AI can help your plant, and where.

We are factory people, not a software company. We start from a KPI that matters to you, check the data you already have, and run a small pilot together. If it does not help, we stop and say so. If it does, we help your team make it part of daily work. We are independent: no licences, no commissions.

  • Tied to factory KPIs such as OEE, scrap and on-time delivery
  • Small pilots before any investment
  • Supplier-risk monitoring and faster cost estimates
  • Independent: no software to sell
Sound familiar?

Signs we could help.

  • You get AI pitches, but none linked to your numbers
  • Your data sits in machines, ERP systems and spreadsheets
  • Pilots start but never reach daily use
  • You have no time or people to try things out
  • You are unsure what is realistic for a plant your size

Not sure where to start? 15 short questions show which area to look at first.

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What we help with

Where we work with your team.

01

Finding the right use cases

A short, practical look at where AI could help your KPIs, ranked by value and effort.

What we do with you

  • Start from your KPIs and losses, not from tools
  • Check what data you already have and how good it is
  • Shortlist and rank a few use cases with your team

What you keep

  • Use-case shortlist with a simple business case
  • Data readiness check
02

Quality & scrap prediction

Using process and measurement data to spot the conditions that lead to scrap, before the parts are made.

What we do with you

  • Link process, machine and quality data
  • Build and test a simple prediction with your engineers
  • Turn it into alerts and actions on the floor

What you keep

  • Pilot results against the scrap baseline
  • Go or no-go decision and a scale-up plan
03

Downtime early warning

Getting a warning before equipment fails, so maintenance can act in planned time.

What we do with you

  • Use existing sensor, stoppage and maintenance data
  • Test early-warning signals on critical machines
  • Build the response into maintenance routines

What you keep

  • Pilot on selected machines
  • Maintenance routine updates
04

Planning, supplier & cost assistants

Helping planners and buyers work faster: supplier-risk monitoring, planning support and quicker should-cost estimates.

What we do with you

  • Pick one task that takes too much time
  • Test a tool or assistant on real work
  • Measure time saved and decision quality

What you keep

  • Pilot results
  • Recommendation on tools, independent of vendors
05

Adoption on the floor

Making sure what works gets used: simple routines, training and clear ownership.

What we do with you

  • Train the people who will use it
  • Build it into daily and weekly routines
  • Agree who owns it after we step back

What you keep

  • Training and routine updates
  • Owner and support plan
How we work

Clear steps, and you decide at each one.

  1. Look

    Diagnose

    We pick one KPI with you and check the data. You get a shortlist and an honest view on what is realistic.

  2. Act

    Improve

    We run a small pilot with your team and measure it against the starting point we agreed.

  3. Keep

    Make it last

    What works becomes part of daily routines, with a clear owner in your team.

Curious whether AI could help your plant? Ask us about it →

Talk to us about practical AI for the factory.

Write to [email protected] with a few lines about your plant. We reply personally to every message.

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Scorecard

Where is your business losing money: purchasing, launches or deliveries?

15 short questions. Free and confidential: your answers stay in your browser.

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Take the free Scorecard