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Scenario · Finance & accountingThe dispute is closed before anyone escalates it
The invoice-dispute agent
A disputed invoice needs an investigation: order, delivery, contract, correspondence. The agent runs it in minutes and comes to a human with a recommendation and the complete evidence.
Executive summary
Invoice disputes drag on for days; evidence scattered across SAP, email and archives.
The agent compiles evidence, proposes a resolution and, once approved, executes the correction.
Resolutions in hours, fewer “just in case” write-offs, better supplier relationships.
SAP FI/MM, email, document archive; UiPath IXP for reading attachments.
A manufacturer, 900 disputes a year
A supplier questions a deduction. The accountant opens SAP, finds the PO, asks the warehouse for the delivery note, digs through three-month-old email. Two days later she has half the picture.
The investigation costs the most, and half the cases end in a write-off “because we cannot prove it”.
The current reality
- SystemThe supplier claim arrives by email
- WaitingSits in the team inbox for 1-2 days
- HumanThe accountant reconstructs PO, delivery, invoice, contract
- HumanChases procurement and warehouse for missing documents
- WaitingWaits for answers between departments
- Error riskA decision without full evidence, or a cautious write-off
- HumanManual posting and a reply to the supplier
The hidden cost of the current process
An hour per case is only the start of the bill
- 75 cases × ~60 minutes of investigation = 75 hours a month of skilled accounting work.
- “No-evidence” write-offs quietly erode margin and are never reported as a dispute cost.
- Suppliers learn that dragging disputes works, so case volume grows.
The cost of doing nothing
You pay for the automation once; the manual process costs you again every month.
The process after automation
- AutomationThe agent reads the claim and attachments (IXP)
- AutomationCompiles PO, delivery note, invoice, contract clauses
- AutomationCompares and proposes a ruling with reasoning
- HumanA human approves or adjusts the recommendation
- AutomationThe robot posts and replies to the supplier with evidence
What the automation handles
- Collecting 100% of evidence from systems and archives
- A resolution recommendation with full reasoning
- Posting, correspondence and case archiving
When a human decides
- Rulings above the amount threshold
- Precedent cases and strategic relationships
- Changes to resolution rules
Before
After
Value model: example assumptions
Johnson Controls, combining UiPath robots with a document-extraction agent, reports 500% ROI and ~18,000 hours saved annually.
UiPath Newsroom, 2025
Business benefits
- Decisions based on evidence, so less margin given away
- Hour-level resolutions strengthen your position with suppliers
- AP gets back to the month-end close
- Every case auditable from claim to posting
Board-level KPIs affected
cost per dispute · days to resolve · write-off rate · DPO
What management gains
- A live dispute register with value, status and bottlenecks
- Hard data on which suppliers generate disputes, for use in negotiations
- Every dispute has a history the whole team can see
Estimate it for your organisation
An illustrative estimate based on your inputs. It models released capacity and is not a savings promise.
Systems in this scenario
Inputs
- Email / supplier portal
- Scans and PDFs (IXP)
- SAP MM/FI
Mientha agentic layer
- UiPath Agent Builder
- UiPath robots
- Maestro™ · Action Center
Core systems
- SAP
- Document archive
- Teams
Human approval: Teams / Action Center
What we deliver
- Analysis of 50-100 historical disputes and ruling rules
- An agent reading claims and documents (UiPath IXP)
- Automated evidence compilation from SAP and archives
- An approval flow with amount thresholds
- Supplier reply templates in 3 languages
- A monthly report: value, time, dispute root causes
What we need to start
- 20 anonymised dispute examples with documents
- Ruling rules and thresholds (even informal ones)
- Access to an SAP test environment
- The AP process owner for 2 workshops
Implementation roadmap
Discovery
We map the process, data and exceptions with process owners.
Design
Target flow, business rules, approval thresholds.
Build
Agents, robots and integrations in your environment.
Validate
Tests on real cases, exception handling.
Go-live
Controlled rollout with human oversight.
Optimise
Monitoring, reporting and continuous improvement.
Duration depends on the number of systems and rules; a single process usually takes a few weeks.
Risk and controls
Autonomy under control
- Recommendations always with reasoning and evidence links
- Amount thresholds: large cases always go to a human
- No postings without approval during the pilot
- Data processed inside your environment
Why now
- Every month is ~€2,400 of investigations that did not need to happen
- Margin pressure makes every cautious write-off more expensive
- AI now reads documents accurately enough for automating such cases to pay off
Why this matters to:
Less margin surrendered and hard data on dispute causes.
75 hours a month back in the team, without hiring.
Supplier conversations based on dispute data.
Questions we usually hear
That is why the pilot starts with 20 of your real examples. IXP reads scans too; anything below confidence goes to a human, flagged with what is missing.
The agent applies your resolution policy. In the pilot every recommendation passes a human, and the report shows where rules are too soft.
Possibly, so we check that first. Below ~30 cases a month we usually recommend only the evidence-compilation module, or advise against the project.
When this may not be the right solution
- Below ~30 disputes a month
- No digital access to source documents
- Ruling rules do not exist even informally
A question for your next board meeting
How many of your last hundred write-offs happened because evidence could not be gathered in time?
Solutions in the library
The same process as an implementation plan
The scenario shows the process with an AI agent on an example company. Library solutions describe the same or a neighbouring process with a value model and an implementation plan.
The finance team moves numbers from PDFs into the ERP by hand.
See the solution Finance & accountingThree-way match exceptions resolved before the payment runPrice and quantity differences are chased by email while supplier payments wait for weeks.
See the solution Finance & accountingPrice and quantity mismatches resolved the day they appearA variance released under payment-run pressure becomes next quarter's price, and nobody negotiated it.
See the solutionWe deliver it through our service AI agents on Microsoft Teams.
The example company in this scenario works in Manufacturing & industry.
How many investigation hours hide inside your disputes?
One anonymised example is enough for us to show how the agent gathers evidence across your systems.
Send us one disputed invoice