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Explainable AI with Arthur

• Know the 'why' behind your AI's decisions
• Quickly diagnose & fix issues with your ML
• Simulate 'What-If' scenarios
• Make 'black box' models transparent

Explainable artificial intelligence (XAI) is a collection of operations and techniques that allows humans to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact, potential biases, and improve performance. XAI helps characterize model accuracy, fairness, transparency, and outcomes in AI-powered decision-making. Explainable AI is crucial for an organization in building trust and confidence when putting AI models into production. AI explainability also helps an organization adopt a responsible approach to AI development.

• Performance monitoring: Track the performance of your models using research-backed metrics.
• Intelligent alerts: Set up intelligent alerts. Never miss an issue with your model inputs or performance.
• Data drift: Identify univariate and multivariate data drift in your ML models for tabular and unstructured data like NLP & CV models.

• Bias detection: Identify biases in your data using univariate or multivariate segmentation.
• Explainable AI: Infer how your models are making decisions using our Explainable AI features.
• Custom metrics: Choose which metrics work for you, including proprietary metrics from our renowned team of experts.

• Model diagnosis: Leverage monitoring and explainability features to diagnose and mitigate issues with your model.
• Counterfactual Explanations: Simulate "what-if" scenarios by adjusting features and observing changes in prediction impact.
• Exportable reports: Increase collaboration across teams with easy-to-digest exportable reports.

Seamlessly integrate models from any development or deployment environment into Arthur’s monitoring platform. With advanced monitoring and alerts across a variety of performance metrics, debug issues faster—so you can spend more time solving interesting problems, not babysitting models.

Arthur works seamlessly with all your favorite data science and MLOps tools. Our platform is model-agnostic and platform-agnostic, which means you get one centralized dashboard for all of your models, no matter which tools you used to build them or where they're deployed.

Quickly get up and running with only a few lines of code, so you don't skip a beat. Arthur can be deployed on-prem, in a cloud environment, or via SaaS.

Arthur is model- & platform-agnostic, meaning it will easily integrate with the tools you use every day.

Monitor all of your models at a glance by connecting them to the Arthur dashboard.

Involve all relevant stakeholders in the model auditing process using easy-to-digest exportable reports and other multi-persona collaboration features.

Set up alerts to track issues in your models, so that you can react as quickly as your business needs you to.

The only platform that supports both structured and unstructured data (NLP & CV) while utilizing the latest and greatest in AI observability techniques developed by experts.

“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, Humana

”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

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