Project Overview

Enhancing Invoice Automation for a US-Based Supplier Relationship Management Software Provider

Our client is a prominent US-based supplier relationship management software company serving mid-market and large enterprises, boasting approximately 200,000 active users worldwide. Their cloud product focused on accounts payable management had successfully automated core invoice processing workflows. However, to meet growing customer demands for higher automation and smarter data handling, the client sought to enrich the product with a new module capable of intelligent invoice data capture that performs reliably under heavy load and scales seamlessly on demand.

Given the technical complexity and strategic importance of this enhancement, the client engaged eSparkBiz for our expertise in distributed modular software development and AI-driven automation to lead the entire product development lifecycle.

The Problem

As the client’s global user base expanded to approximately 200,000 active users, their existing accounts payable management solution began to reveal critical shortcomings in handling the increasing volume and variety of invoice data. The manual processing and validation of invoices—often submitted as scanned documents or PDFs—were labor-intensive, error-prone, and slow. This not only delayed payment cycles but also increased operational costs and risked compliance issues due to inaccurate data capture.

Diverse Invoice Formats and Legacy System Limitations

The client faced challenges in processing invoices from diverse vendors with different formats and layouts, complicating standardization efforts. Their legacy system’s monolithic design made it difficult to introduce new automation capabilities or improve existing processes without risking system instability or extended downtime.

Performance Bottlenecks and Scalability Needs

Under heavy transaction loads, performance bottlenecks impacted user experience and slowed approval workflows. The client required a robust solution capable of processing large invoice volumes quickly while maintaining high accuracy and operational reliability. Additionally, the system needed to dynamically scale to handle fluctuating invoice submission volumes without service degradation, ensuring business continuity during peak times.

Need for Modular, Future-Ready Architecture

The architecture had to allow incremental updates and modular enhancements, enabling the client to remain competitive by rapidly incorporating emerging AI advancements and evolving customer requirements. Seamless integration with the client’s existing cloud product was also essential to avoid disruption and ensure smooth user adoption.

The Solution

Cross-Functional Team for Cloud-Native Invoice Capture on Azure

eSparkBiz assembled a cross-functional team comprising business analysts, web developers, and QA specialists to deliver a robust, cloud-native invoice capture module integrated with the client’s core accounts payable platform on Azure.

Automated Invoice Data Extraction Using OCR

The processing workflow began with invoices arriving either through vendor portals or direct email (PDFs/scanned documents). Using advanced OCR technology, key invoice data such as vendor details, invoice numbers, dates, purchase order numbers, line items, quantities, and prices were extracted automatically.

Enhanced Validation with Azure Cognitive Services

To enhance data accuracy and validation, the team integrated Azure Cognitive Services, which classified, structured, and verified the completeness of invoice information before routing it for approval and payment. This reduced manual intervention and sped up the processing cycle.

Scalable Microservices Architecture on Azure Service Fabric

For scalability and maintainability, the module was decomposed into decentralized microservices hosted on Azure Service Fabric. This architecture addressed service communication, discovery, and monitoring challenges, and ensured the system remained highly available and fault tolerant even under heavy loads. The modular microservices approach enabled independent scaling and continuous deployment, facilitating rapid enhancements without downtime.

The Result

Significant Gains in Accuracy, Efficiency, and User Satisfaction with Scalable Performance
The newly developed intelligent invoice data capture module delivered by eSparkBiz transformed the client’s accounts payable automation. It enabled smart, paperless invoice processing that greatly improved data accuracy and significantly reduced the time users spent entering and correcting invoice details.

As a result, the client saw increased loyalty from existing users and successfully expanded their customer base by offering a cutting-edge feature that enhanced productivity. The system demonstrated stable, scalable performance amid continuously growing workloads, ensuring reliability and responsiveness for a broad and expanding user community.

The solution’s modular microservices architecture laid a solid foundation for future enhancements and ongoing innovation, keeping the client at the forefront of automation technology in the supplier relationship management space.

AI-Powered Invoice Processing with Scalable Azure Microservices

Modernization of Intelligent Invoice Data Capture Module for a Leading Supplier Relationship Management Provider

About The Project