Case Study
Agentic Automation for Accounts Receivable Invoicing and Billing
Improves Accuracy, Speed, Data Integrity and Customer Experience
Intelligent Automation (IA) | UiPath Platform | AI-Driven AR Billing Automation | Engineering & Transportation (Rail)
Use case
A/R Invoicing and Billing
- Geography
- Industry
- Department
- Products
Client Overview
An industry-leading engineering firm operating in the railroad transportation sector manages complex billing requirements for global customers. The Accounts Receivable team was responsible for handling increasing invoice volumes while complying with strict customer-specific billing rules, regulations and compliance requirements.
As demand increased, billing accuracy and speed became critical not only for revenue realization, but also for maintaining strong customer relationships with their largest accounts.
Efficiency of Services
“Our billing requirements and regulations were becoming increasingly more complex, especially for our three biggest customers, and volume was increasing. We looked to eAlliance to help us with automation to address this increasing complexity and demand, rather than onboarding a new employee. Our billing is now seamless with very few errors, and our customer relationship with our three main accounts has improved.”
Average Invoices processed annually
Average Annual labor savings (equivalent to 3.25 FTEs)
Increase in data quality through reduced billing errors
The Challenge
The organization faced growing difficulty billing its three largest customers. Each customer required invoice data to be entered into separate portals, each with unique validation rules and frequent system errors.
Users were often logged out without saving data, resulting in repeated rework and heavy reliance on customer help desks to resolve submission issues. As invoice volumes increased alongside business growth, the manual process became unsustainable.
The company needed a way to manage billing complexity, reduce errors, and meet demand — without adding additional AR staff.
Solution
For the global Engineering, Transportation Rail company this is the solution which we have provided.
eAllianceAI implemented an AI-driven billing automation solution using robotic process automation and machine learning to streamline invoice validation and submission.
Automation validated invoice data before submission, logged into customer portals, entered billing information accurately, and updated the internal ERP system. This reduced portal rejections, minimized manual intervention, and improved billing turnaround time.
The solution enabled the AR team to scale billing operations while improving accuracy and customer satisfaction without increasing headcount.
Process Flow
The AI-driven billing process included:
AI validates billing data against customer-specific rules before submission, reducing portal errors and rejections.
Automation securely logs into customer billing portals and submits invoice data accurately and consistently.
Pre-validation minimizes system “kickouts,” reducing rework and reliance on customer help desks.
Billing data is updated in the internal ERP system, ensuring accurate AR records and reporting.
A workbench enables users to monitor invoice status and manage exceptions efficiently.
"Our billing requirements and regulations were becoming increasingly more complex, especially for our three biggest customers, and volume was increasing.
We looked to eAlliance to help us with automation to address this increasing complexity and demand, rather than onboarding a new employee.
Our billing is now seamless with very few errors, and our customer relationship with our three main accounts has improved.”
The Results
Technology Used: UiPath Platform, Robotic Process Automation (RPA), Machine Learning, ERP Integration
- Significant reduction in billing errors and portal rejections
- Faster, more reliable invoice submission
- Improved customer experience with key accounts
- Reduced dependency on customer help desks
- Increased AR team capacity without additional hiring
By implementing AI-driven AR billing automation, the organization transformed a complex, error-prone billing process into a scalable, efficient operation that supports continued growth.
