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Use cases: concrete applications in your operations.

Eight applications we build, from incoming documents to preventive maintenance. Each shows the problem, what the solution does, who keeps the decision and the result to expect.

Eight applications, from problem to result.

Each card gives the problem; open it to read the use case in five stages, from what the system reads to what is measured, and the result to expect.

Illustrative scenario

Figures are published only once measured with the client. We do not estimate them.

Filter by capability

8 of 8 scenarios shown

  • Document Intelligence, Intelligent Automation

    Incoming document handling

    The problem
    Supplier invoices and mail arrive by email and on paper; a team sorts and keys them before anything can be approved.
    More detailsFewer details

    Read in five stages

    Signal
    Supplier invoices and mail, arriving by email and on paper.
    Understand
    The type of each document and its fields, with a confidence level.
    Decide
    The right approver for each document; uncertain ones go to review.
    Act
    Reading and classifying are automated; payment-related fields are approved by a person.
    Measure
    Manual keying and time to approval, against the starting point.
    Expected result
    Less manual keying and a shorter path to approval.

  • Data Intelligence

    KPI exploration for management

    The problem
    Each monthly review starts with reconciling figures from systems that do not use the same definitions.
    More detailsFewer details

    Read in five stages

    Signal
    Figures from systems that do not use the same definitions.
    Understand
    Indicators reconciled on shared definitions, each figure traced to its source.
    Decide
    Answers to management's questions, in plain language, with their sources.
    Act
    Retrieving and computing are automated; interpretation and decisions stay human.
    Measure
    Time to prepare the monthly review, against the starting point.
    Expected result
    Reviews prepared faster, and discussions about decisions rather than about numbers.

  • Optimization & Decision Support

    Production scheduling

    The problem
    The weekly plan is built by hand; changeovers and late materials are handled from experience.
    More detailsFewer details

    Read in five stages

    Signal
    Order book, changeover matrix, line availability, staffing and raw material arrivals.
    Understand
    Where the plan loses hours: sequence-dependent setups, and the constraint that actually binds this week.
    Decide
    A candidate sequence with its trade-off stated: service level against changeover time.
    Act
    The planner accepts, amends or rejects it. Only an accepted sequence reaches the shop floor.
    Measure
    Changeover hours and on-time delivery, measured on the same lines as the starting point.
    Expected result
    Fewer changeover hours on the same lines, with delivery dates kept in view.

  • Intelligent Agents, Intelligent Automation

    Assistance for internal requests

    The problem
    Purchase and expense requests bounce between requester, manager and finance because information is missing.
    More detailsFewer details

    Read in five stages

    Signal
    Purchase and expense requests, with the rules that apply to them.
    Understand
    What is missing, or outside the rules, in each request.
    Decide
    Complete what existing systems can fill in; flag the rest to the requester.
    Act
    Checks and pre-filling are automated; every spending commitment is approved by a person.
    Measure
    Requests complete the first time, and back-and-forths, against the starting point.
    Expected result
    Requests complete the first time, and fewer back-and-forths.

  • Data Intelligence, Intelligent Automation

    Margin anomaly detection

    The problem
    Discounts outside the approved grid are found weeks later, once credit notes have been issued.
    More detailsFewer details

    Read in five stages

    Signal
    Invoice lines, price-list versions, discount grids and freight costs.
    Understand
    Lines priced outside the approved grid, recurring patterns told apart from isolated errors; below the confidence threshold, they go to review.
    Decide
    Hold the lines before credit notes are issued and correct the price-list fault at its source.
    Act
    Flagging and opening a task are automated; releasing a credit note needs a named approver; renegotiating a contract is escalated.
    Measure
    Margin leakage and detection lead time, against the starting point.
    Expected result
    Anomalies caught before the credit note, and margin recovered.

  • Data Intelligence, Optimization & Decision Support

    Promotional efficiency

    The problem
    Promotions are planned out of habit; it is hard to tell which ones lifted volume without eroding margin, and which only pulled demand forward.
    More detailsFewer details

    Read in five stages

    Signal
    Sell-out by product and outlet, the promotion calendar, price history, and competitor activity where available.
    Understand
    Which mechanics lifted volume without eroding margin, and which only pulled demand forward.
    Decide
    A recommended mechanic, depth and scope per segment, with its expected effect on margin.
    Act
    The plan goes to trade marketing for approval; approved mechanics are written back to the ERP price conditions.
    Measure
    Incremental margin per promotional euro, against the starting point.
    Expected result
    Promotions chosen for the margin they bring, not out of habit.

  • Data Intelligence

    Profitability by customer, product and channel

    The problem
    Revenue, costs, logistics, rebates and discounts sit in different systems, and nobody agrees on which accounts actually make money.
    More detailsFewer details

    Read in five stages

    Signal
    Revenue, cost of goods, logistics, rebates and discounts, drawn from the systems of record.
    Understand
    Profitability reconciled per customer, product and channel, with the definitions written down once.
    Decide
    Which accounts are structurally unprofitable, and what would have to change for them not to be.
    Act
    A review list goes to sales management ahead of renegotiation. Commercial decisions stay human.
    Measure
    Share of revenue under a known margin, before and after.
    Expected result
    A clear view of which customers, products and channels make money.

  • Data Intelligence, Intelligent Automation

    Preventive maintenance

    The problem
    Breakdowns are handled when they happen; intervention history and operator observations are not used to anticipate them.
    More detailsFewer details

    Read in five stages

    Signal
    Sensor readings, intervention history, spare-part consumption and operator observations.
    Understand
    Wear patterns that come before a failure, told apart from normal operating variation.
    Decide
    A ranked intervention list, scored on criticality and on the production window available.
    Act
    Work orders are created automatically; stoppages that affect output need a supervisor's approval.
    Measure
    Unplanned downtime, and failures caught before they have an impact.
    Expected result
    Fewer unplanned stoppages, and interventions planned in the right window.

Recognise one of these? Tell us how it runs in your company.

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