Case Study: Trax Retail reduces data incidents and triples customers with Databand

Trax Retail Drastically Reduces Data Incidents, Increases Customers By 3x with Databand

Trax Retail, a global software company serving retail and CPG customers in more than 90 countries, needed a better way to manage long and complex deep learning pipelines. Its AI-engineering team was spending weeks on training and debugging, while pipeline failures were difficult to trace because the process was effectively a black box. To address these challenges, Trax Retail turned to Databand’s proactive data observability platform.

With Databand, Trax Retail automated and monitored its data and deep learning pipelines through Kubernetes in a single platform, making it easier to orchestrate tasks, compare runs, and identify issues quickly. The results were dramatic: data incidents dropped from about 60% of pipelines to less than 1%, incident detection time fell from days to minutes, and the company was able to triple its customer base while keeping engineering costs flat. Databand also helped Trax Retail manage hundreds of model runs more sustainably and reach about 96% model accuracy.

Trax

Tzoof Hemed

AI-Engineering Team Leader