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Datenschaftler

Use case · solution pattern, not a customer claim

Automated order and document validation

Operations staff manually enter order lines into the ERP and compare item numbers, quantities, delivery addresses, prices, and Incoterms. Errors often surface only in planning, production, or invoicing.

Data landscape

These systems and data need to come together.

The first step is not a new platform for its own sake. It creates traceable access to the sources that shape the process today.

SAP SD or MM, Microsoft Dynamics 365 Business Central, proALPHA, abas ERP, Infor, email, EDI, PDF, Excel, OCR, and customer and material master data.

First project scope

Small enough to test. Relevant enough to decide.

A first step covers one document type, one major customer, or a limited number of frequently ordered items. Extraction and rule validation run in suggestion mode, with an employee confirming the posting.

Frame for a first project
  1. 01

    Constrain

    Select one frequent document type, one relevant customer, or 20 common items.

  2. 02

    Connect

    Match incoming documents with customer, material, and pricing master data.

  3. 03

    Review

    Confirm extracted fields and identified differences before every posting.

  4. 04

    Observe impact

    Observe entry effort, exception rate, customer queries, and transfer errors.

The honest objection

Every customer format is different.

The dependable response

The first step does not need to handle every format. It covers the highest-value or highest-volume segment and makes exception rates transparent.

Conditions

What must be true before technology can create value.

A sound starting point needs clear data, accountability, and boundaries. Missing conditions are made visible rather than hidden.

  1. 01A relevant input segment and its variants are bounded.
  2. 02The required master and validation data are accessible.
  3. 03A clear approval step remains with operations staff.

When personal data is processed, requirements include purpose limitation, data minimisation, access protection, and deletion rules. Works councils and data protection stakeholders should be involved early where the specific use requires it.

Portrait of Umar Qureshi

Personal accountability

10+ years of practice across data and AI.

Umar Qureshi, Data & AI Expert

The technical background spans data engineering and platform architecture through enterprise search and responsibly integrated AI systems. The assessment remains grounded in your process and system landscape.

Meet Umar and the team

Free initial assessment

Which documents cause the most queries and corrections today?

Together, we frame document variants, ERP validation rules, and a safe suggestion mode.

The initial consultation and joint use-case discovery are free and non-binding.