Model Monitoring for

Quantitative Hedge Funds

 

Stay ahead of market shifts with proactive insights, smart alerts, and scalable monitoring that keep your models performing at their peak—so you can focus on what matters most: driving returns.

 

The insights engine behind trustworthy AI

KEY FEATURES

 

Mona | A Model Performance

Insights Platform

 

Mona’s monitoring solution has a unique built-in capability to pinpoint anomalous behaviors

in granular segments, bringing you actionable insights to ensure your models perform at their peak. 

Automatic Performance Insights

 

Dive deep into your data with Mona’s ability to slice through multiple dimensions, isolating anomalies without noise.

Customizable Monitoring

 

Tailor your monitoring schema with bespoke metrics and dimensions, setting up comprehensive monitors for any scenario.

Scalable & Secure Solution

 

Engineered for the most demanding datasets, Mona offers both on-premises
(and air-gapped) and cloud
deployments.

Real-time & Batch Processing

 

Stay ahead with instant anomaly detection and comprehensive historical analyses, ensuring no opportunity for optimization is missed.

MONA BENEFITS

Risk Reduction

 

Protect your investments from unforeseen model discrepancies and errors.

Enhanced Efficiency

 

Streamline your research process, freeing up valuable time for innovation and strategy refinement.

Quick Resolution

 

Rapidly identify and rectify issues, reducing downtime and negative financial impact.

Continuous Improvement

 

Leverage detailed insights to fine-tune models, enhancing performance and profitability over time.

MONITORING USE CASES

 

Specialized Monitoring for

Complex Industries

 

Designed to handle models with the highest levels of risk, scale,

and complexity, Mona empowers teams to maintain control and precision.

Explanations for PnL Leaks

Gain deeper insights into PnL leaks with automated detections and root cause analysis for faster resolutions and system optimizations

Time-Specific Model Deviations

Pinpoint exact times when new model versions diverge, ensuring consistency and reliability.

Inference & Training Data Discrepancies

Ensure model stability by monitoring and aligning inference-time and training-time feature sets.

Feature Correlation Drifts

Detect and address shifts in feature and output correlations over time, maintaining your model's predictive power.

Environment Behavior Comparisons

Identify discrepancies between testing, staging, and production environments, enabling smooth transitions and deployments.

Region-Specific Anomalies

Uncover and rectify unusual model behaviors across different exchanges or regions, safeguarding your assets.

 

Avoid Monitoring’s Number One Enemy: Noise

 

Alert fatigue is the leading cause of monitoring failures—but not for long. Mona’s Common Thread Analysis™ reduces both alert volume and the time needed for issue resolution, enabling smoother and more reliable model monitoring.

Model Operations Time Savings Calculator

This calculator is for informational purposes only and offers general estimates of potential time savings in MLOps processes. Results are hypothetical and not a substitute for professional advice. No guarantees are made regarding accuracy or completeness. Consult a qualified professional for specific guidance.

# of tickets per month

avg. time to address, investigate and

resolve an alert


		

Mona could save you as much as

hours / month

Monitor Your Entire AI Program

 

Gain full visibility and control across all your models –

from AI and ML to predictive analytics, financial models, and beyond.