Know the why and the how behind your AI solutions

Explaining AI outcomes is key to building great AI solutions. When you know why your models are doing something, you have the power to make them better while also sharing this knowledge to empower your entire organization.

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What is Explainable AI ?

Latest AI research, including contributions from our team, brings Explainable AI methods like Shapley Values and Integrated Gradients to understand ML model predictions. The Fiddler Engine enhances these Explainable AI techniques at scale to enable powerful new explainable AI tools and use cases with easy interfaces for the entire team.

Hear from our Data Science team about different Explainable AI concepts.

An illustration of Fiddler's Explainable AI Feedback Loop. Fiddler uses explainable AI to provide useful insights throughout the lifecycle of machine learning models - train, QA, deploy, predict, monitor, and debug.

Cutting-Edge Explainable AI

Trust: Explaining a black-box with another black-box does not establish trust. We ensure transparency through visibility

Production-quality: Fiddler augments top AI Explainability techniques in the public domain including Shapley Values and Integrated Gradients to enhance performance

Enterprise scale: Our solutions are built at enterprise scale and power our industry leading AI Explainability toolset for a robust and reliable experience

Research-focused: Fiddler's paper 'Explanation Game' introduces confidence intervals and contrastive explanations - a significant upgrade to other Shapley Values implementations

Seamless Pluggability

Fiddler's out-of-the-box integrations are easily pluggable with existing data and Al infrastructure making it flexible to use

Plug into any model framework

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Ingest from any data source

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Fiddler Explainable AI Platform

Explainable AI enhance Machine Learning Lifecycle in different stages. In the training stage, Explainable AI helps data scientists to understand how the model is working and how to further improve the model. In the validation stage, XAI supports AI auditors to evaluate the model's fairness. Once the model is deployed, Explainable AI assists IT and MLOps teams to monitor and debug model more quickly and efficiently. Explainable AI also helps business owners to trust models and supports users to provide more useful explanations.Watch demo

Zoom in to the details

Compare distributions across training data, test data and production data.

Slice the data into groups and explain performance discrepancies across groups.

Analyze your AI predictions in relation to the entire data set or just a specific region to find anomalies and drifting data.

An illustration of how Fiddler's Explainable AI helps users to zoom in to the details. Fiddler's XAI provides local and global explanations.

Fiddle with ‘What-if’ Scenarios

Easily understand every single prediction made by your AI solution and spot discrepancies - whether in your training data, your model, or a production inference.

Quickly simulate input scenarios, whether in tabular or text models, to validate and build trust using our patented intuitive interfaces.

Bring in data and models from any platform to explain them in Fiddler using the best interpretability methods available - Shapley Values and Integrated Gradients - made fast, reliable and scalable.

Democratize your findings

Compare distributions across training data, test data and production data.

Generate any type of report you need from compliance reports to marketing dashboards.

Share your reports in multiple formats - through the Fiddler platform, in an email, or through any other tool your team uses.

An image of Fiddler's Explainable AI Solution for ML Monitoring. It is showing the Monitoring dashboard screen of the product. In this tab, a user may see global feature impact, feature interaction, and model frequency.

Build trustworthy and explainable AI solutions with Fiddler.

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