WATCH A DEMO 

See Mona Pinpoint Anomalies in Production Models.

Are evolving fraud patterns, data integrity issues, and silent model failures putting your detection systems at risk?

See how fraud teams proactively monitor AI/ML model performance, surface hidden issues early, and stay ahead of emerging threats in this 6-min demo of Mona's  Model Performance Insights Platform.
Screenshot 2025-05-14 110427

“Mona is already helping us get dramatically more comfortable with our AI deployments. We performed a thorough market evaluation, and Mona has unique capabilities which made it the best fit for our needs.”

Roye Wietzfeld, Head of Digital R&D at Israeli Ministry of Defense

“With Mona, we are able to proactively identify issues in production before our customers are negatively impacted.”

Ohad Parush, EVP of R&D at Gong.io

“As Exceed.ai's business continuously grows, our AI models are required to work seamlessly with a growing number of use-cases and customers. Mona is enabling our growth by assuring that our AI works as planned for all of our use-cases, and alerting us the moment our AI fails or underperforms.”

Igal Mazor, Chief Data Scientist at Exceed.ai

“At Hyro, we strive to always deliver the best value to our customers. Using Mona, even as our customer base and variety of use-cases continue to grow, we can ensure that if any of our bots misbehaves, we’d be the first to notice and fix, before customers are affected.”

Nitzan Bar, Chief Architect at Hyro

Why Mona?

 

Continuous, Proactive

Model Monitoring

 

Mona provides real-time performance insights and early anomaly detection, keeping your models operating at their best.

 

Root Cause Analysis

at Your Fingertips

 

Dig deeper into performance issues with Mona’s intuitive root cause analysis. Troubleshoot faster and improve model outcomes.

 

Continuous, Proactive

Model Monitoring

 

Mona provides real-time performance insights and early anomaly detection, keeping your models operating at their best.

Overwhelmed with alerts?

Mona customers experience as much as 80% fewer monitoring alerts per month.

 

 

Abstract image of time-series data