Use case · AI Studio
Data analysis & reporting
Analyses with built-in quality checks — catching anomalies before they reach the report.
01 · The brief
Thinking across departmental silos.
In most organisations the data sits apart: ERP, CRM, quality management, mailboxes and spreadsheets. Each department optimises for itself — and precisely what lies between the data pools stays invisible.
As a result, questions remain unanswered that nobody asks, because the existing reports could not deliver the answer anyway.
The brief: an agent team that reads across system boundaries, establishes connections and flags anomalies before they end up in a report.
02 · How it works
How the agents work.
The agents read where the data already sits — no additional data silo is created.
Step 01
Connect
Access to the relevant systems — ERP, CRM, quality management, file storage and mailboxes.
Step 02
Check
Completeness, duplicates and implausible values are detected before anything is analysed.
Step 03
Analyse
Metrics and relationships emerge across system boundaries rather than per department.
Step 04
Explain
Not just the number, but the reasoning — with a reference to the underlying data.
03 · The outcome
What changes.
Complaints can be traced back to a production line or a supplier, because ERP, quality management, CRM and mailbox are looked at together.
The quality check is part of the analysis rather than a downstream step — faulty figures never reach the report in the first place.
- Answers to questions nobody could ask before.
- Anomalies are reported, not discovered while reading.
- Every metric stays traceable back to its source.
Does this sound familiar?
In a first conversation we look at your processes together and sketch out where an agent team would make the biggest difference. Free of charge and without obligation.