AI Explainability & Interpretability

Black-box AI systems erode trust and create compliance challenges. Galethis provides explainability and interpretability services that shed light on how AI models reach their decisions. We apply techniques like SHAP, LIME, attention visualization, and counterfactual explanations to make model behavior understandable to technical and non-technical stakeholders alike.

Our Methodology

Our explainability methodology: (1) Explainability Technique Selection based on model type and stakeholder needs; (2) Feature Importance Analysis identifying key decision drivers; (3) Counterfactual Explanation Generation showing what would change the outcome; (4) Explanation Visualization and Reporting for different audiences.