Case Study: 1000x faster Logistics Processing

Case Study: 1000x faster Logistics Processing

Client

A UK-based logistics company.

Problem

The client faced significant challenges with their SaaS backend’s performance, which was inefficient at processing large datasets. The existing optimization system could only handle up to 200,000 variables, restricting their ability to solve complex logistical problems swiftly and effectively. They sought to evaluate the feasibility of handling much larger problems at a faster rate, which would enable them to significantly expand their business operations.

How We Helped

We upgraded the client’s SaaS backend, dramatically improving its efficiency and capacity. Our solution enabled the system to process datasets and solve problems thousands of times faster than before. We enhanced the backend to handle over 50 million variables in minutes, a substantial increase from the previous 200,000 variable limit. This upgrade involved optimising algorithms and leveraging advanced computational techniques and tooling to ensure rapid processing and problem-solving.

Impact

The upgraded SaaS backend now processes complex logistical datasets in minutes, handling over 50 million variables efficiently. This improvement enabled the client to solve intricate logistical problems much faster than before, enhancing their operational efficiency and decision-making capabilities. The dramatic increase in processing speed and capacity provided a significant competitive advantage.