Accelerating Logistics Reliability Through Simulation

A global logistics leader partnered with INTECH to implement an AI-powered Simulation tool that automated sanity testing for its OPS application. The solution reduced manual effort, accelerated release cycles, and enhanced system reliability across multi-site operations.

Client Overview

A Global Logistics Leader Orchestrating Trade at Scale

  • Client

    One of the largest multinational logistics firms with its headquarters in Dubai and operates 172 marine and inland terminals in 51 countries

  • Industry

    Global container logistics including port operations, maritime services and free-trade zones

  • Core Offering

    Terminal operation end-to-end services that enable the transport of 92 million containers each year, and make sure their cargo flows are dependable and time sensitive in the global market

  • Mandate

    Replace manual pre-release checks with simulation-led automated sanity testing to accelerate patch cycles, reduce post-release defects, and strengthen user confidence across multi-site operations

Challenges We Overcome

Release Bottlenecks Undermining Product Stability

Manual Sanity Tests

Time-intensive, repetitive checks slowed every pre-release cycle and diverted QA capacity

Missed Issues

Inconsistent manual coverage allowed defects into production, triggering hotfixes and rollbacks

Delayed Updates

Last-minute discoveries pushed schedules and complicated deployment coordination

User Frustration

Recurrent post-release glitches eroded trust in new builds and updates

Hesitant Adoption

Teams deferred upgrades to avoid disruption, limiting improvements and slowing progress

Solutions

INTECH's Simulation Solution: Automated Sanity Testing at Enterprise Scale

Multi-Site Simulation Coverage

Runs realistic tests concurrently across terminals to ensure comprehensive pre-release validation

Real-Time Monitoring Console

Displays live progress and completed moves in a compact window for instant situational awareness

Performance Tracking Under Load

Monitors CPU, memory, and system operations to validate stability under realistic workloads

Flexible, Site-Specific Configuration

Adapts quickly to different locations and scenarios without code changes

Automated Test Reports & Logs

Produces clear, detailed execution records for review and traceability

Early Issue Detection

Flags defects before release, preventing hotfixes and rollbacks

Tech Stack

The Engineering Stack Behind Reliable Simulation

Core Java

Core simulation and orchestration engine delivering stable, deterministic runs under varied test loads

ActiveMQ

High-throughput message brokering to coordinate components and sequence simulation events without bottlenecks

REST API

Standards-based interfaces enabling seamless integration with existing OPS systems and tools

Hibernate

Robust ORM for consistent, vendor-agnostic data access and dependable persistence operations

SQLite

Lightweight embedded database supporting fast, isolated simulations with minimal deployment overhead

Results

Transforming QA Bottlenecks into Release Agility

Significantly faster sanity testing

Automation cut repetitive manual steps, accelerating validation before every release

Fewer post-release issues

Early detection of defects prevented rollbacks and production disruptions

Shorter release cycles

Streamlined testing enabled timely patch deployment across multiple terminals

Higher user trust and adoption

Stable, consistent updates encouraged quicker acceptance and smoother rollouts

Greater QA efficiency

Freed teams from manual testing, allowing focus on performance and integration scenarios

Real-time visibility

Live dashboards and automated reports improved traceability and release confidence

Business Benefits

Simulation-Driven QA for Confident, Faster Rollouts

  • Faster sanity cycles

    Automated checks accelerated pre-release validation, enabling quicker patch deployment

  • Fewer post-release issues

    Early detection reduced bugs in production and minimized disruptions

  • Higher user adoption

    Stable updates restored confidence and encouraged timely uptake

  • Reliable release cadence

    Consistent validation delivered smoother, more predictable rollouts

  • Stronger trust and satisfaction

    Improved quality led to happier users and sustained confidence in updates

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