Fiddler for Risk and Compliance

Minimize machine learning risks and maintain model compliance at scale

Industry Leaders’ Choice for AI Observability

Maintain regulatory compliance across ML initiatives

Be in control of your ML models and stay ahead of model, data or regulatory changes at your fingertips. 

Accelerate AI time-to-value and scale

Increase ML operational efficiencies

Build trusted AI solutions

Minimize risks impacting your brand and reputation

Improve predictions with context for business alignment

Enable model interpretability for all stakeholders 

Companies trust Fiddler to monitor models for regulatory compliance

Avoid risks that negatively impact your company’s brand and revenue. The Fiddler AI Observability platform supports teams in building out a robust model governance and model risk management framework to meet regulatory compliance, build trust into your AI solutions, and adopt responsible AI. 

Model governance

Adopt effective model governance to minimize risks to your company’s reputation.

Audit all models in your inventory by tracking model performance and data drift at scale. Empower stakeholders with fine-grained control and visibility into model accuracy, and understand the root cause of model degradation. Perform segmentation analysis on anomalies across models to quickly mitigate potential risks and improve operational efficiencies.

Regulatory compliance

Ensure all your models stay compliant through model monitoring. 

Evaluate model performance and how shifts in structured (tabular) and unstructured (natural language processing and computer vision) data attribute to model degradation or model bias. Be alerted to data integrity issues in your pipeline, from missing values to range or data type violations. Quickly respond to regulatory requirements with insight into model changes.

Model risk management

Build a robust model risk management framework with greater model transparency and explainable AI.

Enable regulators and stakeholders across the business to facilitate compliance throughout the MLOps lifecycle and share MRM and risk reports for periodic reviews. Avoid financial risks, fines, or breaches by understanding how changes in model performance or data can alter model predictions.  

"With its clean API and the rich monitoring and analysis tools provided by the UI, Fiddler has greatly reduced the energy barrier to gaining valuable insight on production data. Not only does this provide our team with peace of mind, but we’re equally excited to see how this ‘production-first’ mindset is already informing model improvements in our LTV use cases for more resilient predictions.”
Anthony Anderson
Head of Data Science, Conjura