Vertical AI employee
Clarify master data exceptions
Master Data Exception Agent
The AI employee for missing, incorrect or contradictory master data.
Standard core plus process adaptation
The AI employee has a repeatable core and is adapted to the last 20 percent of your process logic, systems, rules and approval paths.
Existing systems remain leading
ERP, CRM, MDM, CMMS, email, Excel and specialist systems are not replaced. Digamma automates the manual work between them.
Human-in-the-loop
Critical decisions stay with humans. The agent checks, structures, prepares and routes exceptions in a traceable way.
Enterprise readiness
Built to pass corporate buying standards
Large companies do not buy a black box. The first workflow is scoped tightly, connected to existing systems and introduced with clear roles, approvals, data sources and success criteria.
01
No system replacement
ERP, CRM, MDM, CMMS, document repositories and ticketing systems remain the source of truth. The agent automates the manual work between them.
02
Controlled pilot
Start with one measurable process, clear data sources, defined exceptions and a business owner. No big-bang project.
03
Audit-ready handover
Checks, sources, open questions and decision packages are structured so business teams can review them.
04
Approvals stay inside the company
Critical values, new suppliers, compliance decisions and special cases are routed to humans instead of being pushed through automatically.
Value proposition
Fewer data errors, less rework, cleaner processes and better data quality in existing enterprise systems.
Master data errors may look boring, but they create downstream problems in procurement, finance, logistics, production and reporting. The agent clarifies exceptions before they create operational errors.
What problem does the agent solve?
Supplier setup takes too long, materials are created twice, bank data is missing, tax data is wrong or data changes require manual approvals. Teams handle the same exceptions again and again.
The focused entry point
Do not start with a large master data management program. Start by detecting master data exceptions, requesting missing information, checking duplicates and preparing corrections.
Workflow
How the AI employee operates
The agent does not sit next to your systems. It works between intake, rule checks, system matching and human decisions.
Input
Email, ERP, form, ticket or document comes in.
Check
Rules, completeness, ownership and plausibility are checked.
Match
Data is matched with ERP, CRM, MDM, CMMS or document sources.
Route
Standard cases are prepared, exceptions go to humans.
Master Data Exception Agent
The agent does not sit next to your systems. It works between intake, rule checks, system matching and human decisions.
From exception to approvable correction
A new or changed data record is detected.
Mandatory fields, duplicates and contradictions are checked.
Missing information is requested and tracked.
A correction or approval is prepared with full context.
What the AI employee takes over
- Checks new or changed supplier, customer, material or product data.
- Detects missing mandatory fields, duplicates and contradictions.
- Requests missing information from internal or external people.
- Prepares data corrections and approvals for ERP, CRM or MDM.
- Documents clarification history and follows up on open items.
Use case fit
When does this use case fit?
This use case is strongest when operational teams repeatedly check, sort and prepare exceptions before work can move forward.
Many suppliers, articles, materials or customer master records.
M&A, ERP changes or multiple sites have created data quality issues.
Finance, procurement or logistics face repeated downstream errors from bad data.
Strong fit: industry, retail, logistics and mid-sized companies with ERP complexity.
Strong signals in a first conversation
- Many manual master data corrections or approvals.
- Downstream errors in procurement, finance, logistics or reporting.
- Multiple systems or locations create contradictory data.
Find where master data exceptions slow down operations
In the intro call, we identify the narrowest measurable starting point around duplicates, mandatory fields, approvals or data corrections.
Book intro callConnectors
Connects to your existing business software
The AI employee does not replace your core systems. It works with ERP, CRM, tickets, documents, databases and collaboration tools.
Integration map
Where the agent works in your IT landscape
The AI employee connects intake, rules and core systems. That creates automation without replacing ERP, CRM or specialist software.
01
Inputs
- ERP
- Forms
- Documents
02
Digamma AI employee
- Check
- Match
- Summarize
- Route
03
Core systems
- ERP / CRM
- MDM / CMMS
- Tickets
- Databases
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Prepare maintenance work orders
The AI employee that turns maintenance and service tickets into actionable work orders.
Open page →Economic lever
What does it cost if this process stays manual?
Many operational AI projects do not pay back through big visions. They pay back through recurring minutes lost every month in checks, follow-ups and preparation.
Cases × minutes per case ÷ 60 × loaded hourly cost
Directional estimate, not a fixed savings claim. All values are calculated monthly figures. In the intro call, we replace these assumptions with your real volumes, cycle times and approval logic.
Manual process cost per month
€9,800
Calculated monthly values
The displayed amounts are estimated monthly costs based on your inputs.
Manual hours per month
140
Potentially relieved cost per month
€4,900
Check with real numbers
Book intro call