Measure model performance against critical business metrics
Detect, diagnose, and react to data drift with both structured and unstructured data before it impacts results
Proactively improve model accuracy
Build trust with valuable insights into how your models are making decisions
Ensure compliance in your ML systems with local explanations for model outputs
Leverage context around model predictions to drive stronger, more actionable outcomes
Proactively monitor for bias with custom fairness thresholds
Compare model outcomes against fairness metrics for specific groups
Continually improve the fairness of model outcomes without re-deploying
Fortune 100 leaders across financial services, healthcare, retail, and tech trust Arthur to monitor and improve their ML models to drive business impact.
"Thanks to Arthur, we know that our preventative care models are fair, and that we can catch any potential issues before they impact our members…and the Arthur platform allows us to detect and fix data drift before it becomes a real problem."
Chief Analytics Officer
"The biggest challenge is looking at this from a reputational risk perspective. The last thing we want is to be on the front page of the news with a bias issue."
Global Tech VP
"Arthur is 6-9 months ahead of the competition and there was a clear preference for their UX among our data scientists."
Head of Global Artificial Intelligence