Complaint management with AI: patterns across many cases
Individual complaints are handled carefully. What twenty complaints have in common is rarely seen, because the answer is spread across several systems. Onagero brings it together.
- Runs on your server
- Reads only, never writes
- GDPR ready
- First result in weeks
In short
Onagero links complaints to order, batch, line, shift and supplier and sorts the free texts into categories that your QM defines. The result is a tool that shows clusters, traces every complaint back to its production and prepares drafts for reports.
How your team describes it
Your experts say what they need in their own words. Onagero finds the right data and builds the tool in a test stage; after your release it runs in operation.
„Put all complaints next to batch, line and supplier and show me which cases belong together.“Evaluate complaints, as a tool in the browser
What the tool takes over
Three steps done by hand today. The tool your team builds with Onagero then does them itself.
Linking
Complaint, delivery note, order, batch and production data, via keys that we check in the pilot.
Organizing
Free texts are assigned to categories that your QM defines. Each assignment is marked as a suggestion until it is confirmed.
Showing clusters
Complaints per characteristic over time: item, line, material, supplier, customer.
Typical situations
This is what the value looks like day to day.
Customer reports the same thing for the third time
The tool shows the two earlier cases, their batches and what was found at the time.
Quarterly review
The most frequent defect patterns with trend, without a hand-built table.
Supplier complaint
Defects traced back to a purchased part are linked to goods receipt and supplier.
8D in preparation
The facts of the case are ready: affected orders, batches, similar earlier cases.
Which data is needed
- Complaints with free text, customer, item and date
- Delivery notes and orders
- Batch or lot tracking, where available
- Optional: inspection data and goods receipts
Only what your IT releases is read. Names are masked in the development stage. How the data path works
What you end up with
A tool that evaluates complaints by confirmed categories and characteristics, tracks every complaint back to production and shows similar earlier cases for a new case.
Start with one problem.
Keep the capability.
No AI transformation. One real process, solved on your data in a few weeks. Your team solves the next one itself.
How your price is formed
After the demo you get a fixed offer. Scope, goal and price are set in writing before it starts.
One real problem, the data sources it needs, your Onagero environment on your server, and the first solution, built with your team and measured against the agreed goal.
- Scope, goal and price in writing before the start
- First running solution in a few weeks
- Your data and results stay exportable at any time
Operating the platform on your server: monitoring, reviewed updates, backup and rehearsed recovery, and maintenance of the connections when systems change.
- Begins only once the start has reached its goal
- Your team builds further solutions itself, in the same environment
- Roles, releases and logs included
What you can rely on
The tool reads, computes and shows. These things it never does, and that is in the contract.
- Onagero does not decide on blocking, recall or acceptance of a complaint.
- It adopts no category without confirmation by your QM.
- It does not replace your CAQ or document system.
Questions about Evaluate complaints
How well does the AI organize free texts?
We measure that in the pilot on your own complaints: how many suggestions your QM confirms unchanged. Each assignment remains verifiable, down to the original text.
What about complaints in English?
The tool can organize multilingual texts. The original text is kept.
How far back makes sense?
As far as the data is reliable. Often two to three years; we check that together.
Do customer names appear in the tool?
The evaluation usually needs customer names. Names of contact persons in free texts are masked in the development stage.
Can the tool fill in 8D reports?
It prepares drafts. The report is released by your team.
A direct line
Write two sentences about Evaluate complaints. You get an answer from a person who builds the tool themselves.
Prefer something structured? The fit check asks seven questions and tells you right away whether a pilot fits.
Which problem would
your team solve first?
Show us a real process. We will show you how it could look with Onagero.
Book a demo →