Client
A US-based freight brokerage services provider
Industry
Logistics & Transportation
Services
IT audit, IT consulting, data platform assessment

Challenge

Our client, a major freight broker in the United States, was struggling with an outdated, custom-built transportation management system (TMS). Due to its inconsistent development, the monolithic system architecture lacked modularity, encompassing diverse functions such as load monitoring, user coordination, and partner integration. This resulted in numerous failures, performance bottlenecks, and the implementation of inefficient processes. These technical limitations were exacerbated by inefficient development processes. After acquiring another logistic brokerage company, the platform strain increased, as did internal frustration. The merger exposed significant gaps in system scalability and resilience, resulting in a wave of employee departures. Recognizing the urgent need to modernize, the client contacted ITRex for a comprehensive IT infrastructure audit. With a long-standing partnership in place, the client relied on ITRex to provide a clear roadmap for stabilizing operations and enabling future growth.

Solution

To meet the client's tight timeline and complex requirements, ITRex put together a cross-functional audit team that included a senior solution architect, lead business analyst, data consultant, DevOps specialist, and QA lead. They worked together to create a detailed audit plan that covered infrastructure, databases and data platforms, development and QA workflows, and architecture. Over a six-week period, our team held five in-depth workshops with client stakeholders, allowing for simultaneous analysis of technical systems and business requirements. The core assessment areas included:
Cloud infrastructure: resource allocation, network setup, storage integrity, backup strategies, and data security protocols
Data platforms and database management: data models, data pipelines, retention policies, synchronization across sources, and consistency of key business data
Delivery & deployment: CI/CD pipelines, Git workflows, QA workflows, release plans and stability, DevOps tooling
Application architecture: tech stack versions, component structure, code quality, and architectural best practices
We also broadened the scope of the audit to include the platform's functional structure and developed a disaster recovery plan to ensure business continuity in high-risk scenarios.

Data platform assessment: streamlining analytics, reporting & governance

As part of the overall infrastructure audit, ITRex conducted a data platform assessment to determine the system's readiness for dependable analytics, reporting, and data-driven decision-making. Our consultants concentrated on five key dimensions:
Data processing & pipelines. We investigated the quality, timeliness, and structure of the data flows.
Data modeling practices. Our team assessed the consistency and clarity of business logic across models, identifying redundancies and inefficiencies.
Reporting layer audit. ITRex examined current dashboards and KPIs to identify performance issues, broken logic, and governance gaps.
Platform reliability & scalability. The ITRex data consultants identified the causes of delayed updates and pipeline instability, which affected the client’s daily operations and processes.
Future-readiness. We explored how the data platform could evolve into a centralized operational data hub (ODH) to support the customer’s long-term analytics and AI implementation goals.
This analysis produced a standalone data platform assessment report with detailed findings, issue summaries, and tailored recommendations. We also developed a phased roadmap for overhauling the data environment, whether by improving the current system or migrating to a modern data platform solution. The IT infrastructure audit deliverables included the following:
Infrastructure diagram that depicts all IT systems and their interconnections
Application component map, which outlines module relationships, dependencies, and points of failure
Data platform architecture diagram detailing ingestion, processing, modeling, and reporting workflows
Bottleneck analysis that identifies key system constraints and proposed fixes
Disaster recovery plan, which is designed to mitigate risk and ensure business continuity
Cost optimization strategy that highlights potential areas for infrastructure savings
Transformation roadmap covering immediate fixes and long-term modernization steps across the platform
IT infrastructure audit for logistics
IT infrastructure audit

Impact

Improved visibility into overall system performance, code quality, and architectural flaws
Prioritized plan for system stabilization and future-proofing its architecture
A solid foundation for AI ODH implementation that supports structured, reliable reporting and improved operational insights
Stronger readiness for the client to scale operations and manage future system complexity

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