Enterprise Application Integration for a US Transportation Company

About Our Client

The end Client is a US passenger transportation company.

Disconnected Systems Were Slowing Down Transportation Management

Before turning to ScienceSoft, the Client used to have three enterprise systems — each vital to its daily operations — that functioned in isolation. This led to process inefficiencies, data inconsistencies, and operational blind spots.

• A dispatch system managed vehicle assignments, driver schedules, ride details, and trip statuses in real time.
• A fleet management system tracked vehicle specifications, maintenance schedules, fuel usage, and compliance requirements to maintain optimal fleet performance.
• An onboard video surveillance system captured and stored in-vehicle video footage for security and regulatory needs.

The Client needed a reliable solution to connect these systems, which would improve data accuracy and streamline operations. Additionally, the Client considered the possibility of evolving this solution into a SaaS product in the future, which required a scalable and flexible software architecture from the start.

Cloud-Based Middleware to Integrate Transportation Management Systems

ScienceSoft’s team of two .NET developers and an Azure DevOps engineer began with a comprehensive analysis of the data managed across the Client’s three previously disconnected systems. They identified multiple data quality issues, including inconsistent field naming, varying data formats (e.g., mileage recorded as "80" in one system and "80.0 mi" in another), duplicate entries, and incomplete records. To address this, the team mapped data entities across the systems and designed custom data transformation rules to normalize, clean, and enrich the incoming data.

Early in the process, the team also identified that the available API documentation was outdated and incomplete, which created uncertainty around data exchange formats and endpoints. To address this, the engineers collaborated closely with the Client’s in-house consultant to clarify undocumented behaviors, update existing API specifications, and fill in the missing details — ensuring a reliable foundation for integration.

With the structured data integration framework in place, ScienceSoft’s engineers developed a custom cloud-based integration middleware that leverages scheduled cron jobs. By strategically staggering job execution, the team was able to distribute processing load over time and reduce the risk of resource contention during peak hours, ensuring reliable data synchronization across all three systems.

To prepare for future expansion, including the potential evolution of the system into a multi-tenant SaaS product, the developers involved ScienceSoft’s lead solution architect, who reviewed and refined the architecture throughout the development process. He evaluated the efficiency of data processing flows, validated the separation of configuration, transformation logic, and execution layers, and more.

Synchronized Enterprise Systems Reduced Data Errors and Sped Up Business Operations

After a six-month engagement with ScienceSoft, the Client received a reliable middleware solution that now connects its three core enterprise applications. It has enabled seamless real-time data synchronization across all three systems, enhanced data accuracy and visibility across the enterprise, and minimized the need for manual data transfer and error correction.

Now, the transportation company benefits from streamlined workflows, improved fleet management, and a system ready to evolve into a SaaS product when needed.

Technologies and Tools

.NET, Azure Kubernetes Service (AKS).