Monitor, Explain and Analyze your AI in Production.
Fiddler's Explainable AI Platform unlocks the AI blackbox with continuous Monitoring and 360-degree Explainability.
Get complete visibility into your AI, know the "why" behind AI decisions, drive business with actionable insights from AI.
True explainability in AI is understanding, analyzing, validating, and monitoring your AI solutions at scale, continuously.
Monitor AI performance
Save time in tracking and diagnosing AI performance issues with quick and actionable alerts.
Save money with faster turnaround on AI issues.
Ensure optimal AI performance by tracking data drift and outliers.
Understand AI predictions
Build trust by explaining the why and how behind AI predictions.
Democratize confidence in your AI by sharing explanations with everyone.
Take control of your AI with a human in the loop to audit your predictions.
Analyze AI behavior
Ensure solution fidelity by understanding AI behavior across your data set
Assure high-quality by evaluating how specific data regions impact your AI models.
Spot test predictions by fiddling with their inputs to gauge impact of each input.
Validate AI compliance
Ensure your AI solutions are compliant with industry regulations.
Reduce compliance costs with tools to assess bias and increase AI understanding.
Make customers happier with responsible AI solutions using integrated explainability.
Best in Class Explainability
We believe explaining a black-box with another black-box does not establish trust.
Fiddler augments top explainability techniques in the public domain including Shapley Values and Integrated Gradients. Our solutions are built at enterprise scale and power our industry leading explainability toolset.
Fiddler's paper 'Explanation Game' introduces confidence intervals and contrastive explanations - a significant upgrade to other Shapley Values implementations.
I have been working on Machine Learning for over a decade and I can say what Fiddler team is building is truly unique and a really needed solution for organizations that need a Trusted AI Platform.
Today, most ML models, especially in Deep Learning, are black boxes for both its developers and especially its users. With Fiddler’s new technology, I can see how those models work and iterate on improving them.
