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Our method

Your process first. Then AI.

We analyse how work actually gets done at your company, quantify what it costs, then integrate AI where it brings a measurable gain.

Animated scene: this week’s production schedule as it is planned today — a clash on the machining station, idle assembly, two orders delivered late — then its quantified cost (≈ €12,400 per week). Only then does AI propose a sequence that meets the promised dates; the planner approves it, and all five orders ship on time: ≈ €12,000 per week recovered.

Common situations

Does this look like your day-to-day?

  • Admin and finance

    Supplier invoices, quotes and purchase orders re-keyed by hand into the ERP.

    Impact

    Input errors, late payments, team hours lost.

  • Production

    The shop-floor schedule is redone by hand every morning as soon as a rush order or breakdown disrupts the sequence.

    Impact

    Idle machines, overtime, delayed deliveries.

  • Logistics and inventory

    Stock levels are checked in the ERP, corrected in Excel, then confirmed by phone with the warehouse.

    Impact

    Stock-outs or overstock, supplier orders placed too late.

  • Quality and maintenance

    Non-conformance reports and intervention notes written by hand, rarely used afterwards.

    Impact

    The same defects and breakdowns keep coming back, with no root-cause analysis.

  • Customer service and sales admin

    Lead-time, pricing and order-tracking requests depend on whoever knows the file.

    Impact

    Slow replies, customers chasing, workload concentrated on one person.

  • Reporting

    The week’s KPIs are rebuilt from ten different files.

    Impact

    Decisions made late, on figures that are already out of date.

The common thread: repeated decisions, made on scattered information. That is exactly where AI delivers a measurable gain.

The approach

From the observed problem to the measured result

Five steps, one common thread: the objective set at the start guides the project and measures its success at the end.

  1. Observe the real process

    We look at who does what, in which tools, with which data and which exceptions.

  2. Quantify the problem

    Time spent, errors, delays: we set a measurable objective before talking about a solution.

  3. Put AI in the right place

    We identify the steps where AI brings a gain and those that stay under human control.

  4. Test in real conditions

    The solution runs on a limited scope, in your tools and with your data.

  5. Measure and extend

    We compare the result against the same indicator as at the start, then we extend.

The role of AI

What AI does in your processes

  • Read your documents

    Invoices, purchase orders, contracts: AI extracts the right information, whatever the format.

  • Understand requests

    Emails, forms, WhatsApp: AI identifies the request and routes it to the right person.

  • Find information

    Your teams query your internal documents and get an answer that cites its source.

  • Prepare the action

    AI prepares the entry, the reply or the follow-up in your software, and your teams approve.

Sensitive decisions stay in your hands. And if AI isn’t justified, we tell you.

Production

Reliability is decided in the exceptions

Your business produces surprises every day. We plan for them from the design stage.

  • Unreadable document or unexpected case

    It is flagged to the right person.

  • Irreversible action

    Human approval is mandatory.

  • Traceability

    Every action and its source are recorded.

  • Monitoring

    Costs and performance are measured over time.

What now?

Is a process taking too much of your time? Describe it to us.

Who is involved, with which tools, where it gets stuck. We’ll tell you whether AI has a place, and where.

First conversation with no commitment.