Explainable Machine Learning
simMachines provides the only machine learning software that can provide “the Why” behind every prediction at the speed and scale necessary to drive marketing, fraud, and identity applications with full transparency.
Accurate
Our explainable predictions will match or outperform any other method
Justifiable
Predictions with the Why provide trust and understanding through transparency
Actionable
The weighted factors behind every prediction reveal actionable intelligence that drives transformative business impacts
Measureable
Continuous learning enables every action’s predictive drivers to constantly be measured and automatically adjusted
Explainable AI (XAI) Revolutionizes Marketing Segmentation
Similarity based explainable AI revolutionizes segmentation for customer marketing and audience creation for ad campaigns, providing unparalleled predictive power and contextual relevancy.
Similarity-based Machine Learning
simMachines achieved world-renowned breakthroughs in scale and speed with similarity. Unlike decision trees or neural networks, similarity methods make predictions explainable, understandable and actionable.
Transparency & Insight
simMachines is the only Machine Learning technology that provides “the Why” behind every single prediction we make. Our technology then groups predictions into dynamic predictive segments to enable business users to take insight driven action with great precision and speed.
XAI Analytic Workbench Applications
Our technology helps large global enterprise realize significant performance gains, efficiencies, insights and improved relevancy and customer experience in tackling marketing, fraud and identity applications. Click here for our XAI Analytic Workbench fact sheet.
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Dynamic Customer Segmentation: The Next Evolution in Marketing The current state of customer segmentation is quite antiquated in an age where customers expect immediate relevant communication from brands regularly.
*Capture The Customer Moment With Dynamic Predictive Segmentation, a January 2018 commissioned study conducted by Forrester Consulting on behalf of simMachines
