Ai4G solutions

Data quality, governance, traceability and compliance

Ensure your data is reliable, controlled and auditable

We apply quality controls, reconciliation, lineage and security, and generate audit evidence so that information can be used confidently in processes, reports and decision-making.

Tell us about your case

The challenge

When having data is not enough: you need to be able to trust it

Duplicates, incomplete values and different rules across sources can affect decisions and deliverables. Without traceability, it is also difficult to explain where an indicator comes from or which controls it has passed.

  • Errors are detected after a report has been published.
  • Sources contain duplicate or inconsistent records.
  • There is no clear view of the origin and transformation of indicators.
  • Audit evidence has to be gathered manually.

The outcome

Validated information and audit evidence available when needed

We define common rules and an auditable process so that data, access and deliverables can be checked before and after use.

  • Automated validation before publication.
  • Reconciliations with differences classified.
  • Visible lineage from source to indicator.
  • Reproducible exports and audit packs.

What we do

Capabilities applied to your operations

We select and combine the capabilities required according to the challenge, existing systems and the outcome the project needs to deliver.

  • Quality and validation framework

    We check required fields, formats, ranges, null values, duplicates and cross-field rules.

  • Reconciliation and integrity

    We compare sources and classify matches, missing entries, differences and incomplete deliverables.

  • Governance and lineage

    We document sources, owners, transformations, rules and governed models.

  • Auditing and audit evidence

    We prepare documents, logs, versions and indexes with timestamps and traceability.

  • Controlled access and exports

    We apply roles, anonymisation, field selection and access logs.

Use cases

Practical, measurable examples

  • Pre-publication checks

    A report is not published if it contains future dates, duplicate identifiers or out-of-range values.

  • Auditable reconciliation

    Records are classified as matching, unique to one source, or matching with differences.

  • KPI traceability

    A user can verify the source of an indicator, its transformations and the controls applied.

  • Review pack

    The system gathers documents, logs and results by case and produces an index ready for audit.

How we work

From the challenge to a solution designed to scale

  1. Assessment

    We identify the challenge, the users involved, the available data and the business outcome the solution needs to deliver.

  2. Functional MVP

    We build an initial usable version to validate the approach with real cases, measure its impact and adjust priorities.

  3. Production rollout

    We integrate, automate and strengthen the solution so that it can operate securely, with traceability and the capacity to evolve.

  • Reliability

    Teams work with data governed by known rules and repeatable controls.

  • Compliance

    Access, exports and audit evidence follow defined, reproducible criteria.

  • Traceability

    The origin, changes and use of information can be explained and reviewed.

Let’s discuss your case

Define a practical, measurable initial scope.

Request an assessment