Use cases / Data cleansing

Cleanse incomplete master data

Outdated addresses, missing details, unstructured legacy documents: Our solution cleanses your data at scale - pre-filled for the customer, checked, confirmed and written back into the core system, audit-proof.

See the journey
in batch pre-filled for the customer written back, audit-proof
Batch

The starting point

Your master data is better than its reputation - but not complete.

Over the years gaps appear: missing tax IDs, outdated addresses, unclear entries, documents only on paper. For reporting, contact and regulation that is a growing risk.

Status quo

Before: data gaps sit untouched

  • Missing and outdated fields only surface when it's too late.
  • Re-collection happens by mail merge and manual filing.
  • Legacy documents sit as paper or PDF - not analyzable.
  • Nobody knows how many records are truly complete.
After

After: a cleansed, complete data set

  • Incomplete records are detected and bundled automatically.
  • Customers confirm their data pre-filled via a secured link.
  • Legacy documents are scanned, read and structured.
  • Cleansed data flows back into the core system, audit-proof.

The process journey

From the data gap to a cleansed data set.

Five steps, one journey - for cleansing entire data sets in batch. Click through.

In the builder

Data cleansing - fully digital.

Cleanse entire data sets as a guided campaign - pre-filled, confirmed and written back into the core system, audit-proof.

The result

What changes for you.

Complete, current master data - cleansed in batch, with no re-keying in your team.

1 campaign

Entire data sets cleansed in one run - instead of case-by-case chasing.

No
re-keying

Confirmed data flows back automatically - your team types nothing.

Live in
days

From analysis to a running campaign - without a long IT project.

Which data set would you like to cleanse?

Describe a data set with gaps or outdated entries - we'll show the cleansing on your concrete case.