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Engineering updateFinancial continuity, from the foundations.
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Use cases

Where the approach applies

Concrete operational problems, each with an explicit status. The internal demonstrator uses synthetic data and illustrates FxChain boundaries without executing the core. Client references require written consent.

Read the internal exampleDiscuss a use case
Categories

Problems the approach addresses

The status says how far each category has gone: implemented locally in an internal lab, planned, or still in research.

  • Implemented locally

    Finance operations review

    Deciding which postings need a human review, with a trail that can be checked from the data to the action.

    Internal example
    Supplier invoice review on a synthetic finance dataset
    Client references
    None published yet
  • Planned

    ERP migration assurance

    Showing that migrated financial items match the approved scope, with every gap known and explained.

    Internal example
    None yet
    Client references
    None published yet
  • Planned

    Data and AI pipeline qualification

    Showing what a new pipeline version changes in business results before it is switched on.

    Internal example
    None yet
    Client references
    None published yet
  • Research

    Agent actions under mandate

    Bounding what an automated agent may request from an operational system, and recording what was actually observed.

    Internal example
    None yet
    Client references
    None published yet
  • Research

    Laboratory protocol traceability

    Linking a result to the protocol, parameters, tool versions and reviews that were actually used.

    Internal example
    None yet
    Client references
    None published yet
Internal example

Measured in the lab, with its limits

Internal examples run on synthetic data. The published demonstrator illustrates FxChain boundaries without executing the core; its measurements are lab results.

Implemented locallyMeasured on 18 September 2026

Supplier invoice review on a synthetic finance dataset

An internal lab on synthetic finance data follows one bounded action through a simulated target. FxChain boundaries are illustrated; the FxChain core is not executed.

  • 1,175,515

    journal lines prepared by a distributed data-processing engine, run in local mode

  • 65 of 65

    defects injected into the source and quarantined, each with its reason

  • 0

    unbalanced documents reaching the business layer

Synthetic data from a seeded generator, without client systems or data. FxChain boundaries are illustrated; the FxChain core is not executed in this demonstrator.

Read the full example
Client references

How a client reference is published

References will be listed in their category. Each one follows the same five steps.

  1. 1

    Scope

    The question, the data and the measure of success are agreed with the client before any work starts.

  2. 2

    Pilot

    The work runs on the client's own environment and data, under its access rules.

  3. 3

    Measure

    Results are measured together, and their limits are stated in the same terms as for the internal examples.

  4. 4

    Consent

    The client approves in writing its name, the figures and the wording, or chooses an anonymous description.

  5. 5

    Publish

    The reference appears in its category with its status, its date and what it does not show.

No client reference is published today. This page shows no client name, logo or figure until the client has approved it in writing.

A problem that fits one of these categories?

Describe it in a few lines. The answer states what can be measured, on which data, and what cannot.

Discuss a use caseWhat exists today