Build Your Framework for Responsible AI
Deliver a monitoring framework for responsible AI practices with visibility into model behavior and predictions.
Provide deep actionable insights using explanations and root cause analysis.
Give immediate visibility into performance issues to avoid negative business impact.
Monitor and validate tabular and unstructured ML models faster prior to launch.
Solve challenges such as data drift and outliers using explainable AI.
Get real-time alerts when model performance metrics drop for an immediate fix.
Connect model performance and predictions to business KPIs.
Empower multiple teams to fix issues with a unified dashboard and shareable views.
Provide explanations for all model predictions, delivering explainable AI at scale with easy-to-use interfaces.
Supply the best explainability methods available, including Shapley Values and Integrated Gradients.
Bring your own explainers for faithful explanations.
Query and replay past incidents for enhanced debugging.
Understand model behavior with local and global explanations for multi-modal, tabular, text, and computer vision inputs.
Drill-down to understand where a model is failing and how to improve it.
Test new theories using what-if analysis with predictions on altered inputs.
Mitigate risk with access to past, present, and future model outcomes.
Compare model performance metrics and predictions across local, regional, and global data.
Make every model explainable in human-understandable terms.
Detect and evaluate potential bias issues within training and live production datasets.
Access standard intersectional fairness metrics such as disparate impact, equal opportunity, and demographic parity.
Select multiple protected attributes to detect hidden intersectional unfairness across protected classes.
Operationalize the MLOps lifecycle to ensure the creation of responsible AI.
Reduce the TCO of a homegrown solution, estimated at $750K over three years.
Deploy a MLOps solution designed for enterprise scale with built-in security and support.