AI IN PRACTICE / COMPLAINTS MANAGEMENT

Complaints management

Trace exposure. Track corrective action.

Illustrative process scenarios — not customer references. Feasibility, benefits and approvals need to be established for the specific organisation.

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ILLUSTRATIVE SCENARIO

Trace potentially affected batches after a complaint

From the reported part to stock and customer shipments: AI supports intake, while traceable links establish potential exposure.

UNDERSTAND THE AI

What happens behind the scenes.

TECHNICAL INSIGHT
POSSIBLE SOLUTION DESIGN

Document AI · Entity extraction · Rule-based traceability

What does the AI actually do?

AI reads complaint text and label images, identifies part, batch and serial numbers and prepares the trace. It then explains the evidenced relationships in plain language.

How the solution works

  1. 01
    Capture identifiers

    OCR and extraction models read the message and label. Format and master-data checks expose invalid or ambiguous identifiers; uncertain readings require confirmation.

  2. 02
    Follow recorded links

    Database queries follow confirmed links from serial number to production lot, material batch, stock movement and shipment. These links determine the exposure set.

  3. 03
    Explain the evidence

    An LLM summarises the returned paths and gaps. Each item remains traceable through its identifiers and records to the source batch.

What value can it deliver?

Less intake and compilation effort and faster visibility of potentially affected stock and shipments. More precise evidence can avoid unnecessarily broad holds where traceability is complete.

A concrete example

Illustration: a label identifies a serial number, which leads to a material batch and related shipments. A missing inventory link is explicitly shown as a data gap.

Technology, setup & operation

Relational queries or a genealogy graph perform the core trace. AI assists intake and explanation; it cannot fill missing material-flow links by assumption. Complete transaction records and stable identifiers are essential.

Illustrative solution design. The final architecture depends on data, systems and pilot evaluation.

Starting situation

A customer reports a crack in a component. The serial number is in an email and a photo shows the label. Quality needs to identify the material batch, locate related parts and determine which shipments require review.

How the workflow could look

  1. Confirm identity

    The assistant extracts part, serial and delivery numbers from the message and image. Staff confirm uncertain readings before tracing starts.

  2. Trace material flow

    Rule-based links connect production lots and material batches with inventory and shipment lines. Gaps in traceability remain explicit.

  3. Coordinate action

    A working list records potentially affected positions, owners and deadlines. Quality decides on inspections, holds and customer communication.

Illustrative work product

A reviewable exposure list with the connection to the source batch, open status and assigned actions.

FROM SCENARIO TO A PRACTICAL NEXT STEP

Which process deserves
a closer look?

Together, we can clarify the current process, available evidence and a useful pilot. My contribution: structure, priorities and alignment between business teams, IT and implementation partners.

Discuss a use case