Case Study: Fiverr achieves confident AI monitoring and faster issue detection with Mona

Fiverr utilizes a highly configurable tool to enable monitoring for dozens of models in a myriad of business functions

The customer, Fiverr, faced the challenge of monitoring its diverse and growing portfolio of AI models to proactively detect performance issues and ensure they were driving business growth. To address this, Fiverr’s Director of Data Science, Yuval Ben Zion, evaluated several AI monitoring solutions, seeking a flexible platform that could handle vastly different use cases from real-time search ranking to internal batch processing models.

The vendor Mona provided its monitoring solution, which was selected for its high configurability and ability to integrate with Fiverr's tech stack. Mona's platform allowed Fiverr to easily define custom metrics and track model performance across multiple environments. Within 12 months, Fiverr expanded its monitoring to 15 model use cases using Mona, enabling the team to detect issues before they impacted key business KPIs and ensuring optimal AI performance.

Fiverr

Yuval Ben Zion

Director of Data Science