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Open-Source Library for AI Model Explainability
Artificial intelligence can predict outcomes, but its inner workings can be a mystery. Facet, an open-source library by BCG X, cracks complex AI algorithms, uncovering how variables contribute to a model’s reasoning—and how you can get better results.

About Facet
Predictive AI is not a magic crystal ball. It’s based on science and has a long track record. But for many business leaders, the analogy does raise a point. Without understanding complex machine-learning (ML) algorithms, how can we truly trust the models—let alone base strategies upon them?
Facet, an open-source library by BCG X, takes a unique approach, showing how relevant features interact to determine key outcomes. This helps data scientists avoid common misinterpretations of ML models. And it reveals the variables that matter most. By explaining AI, Facet informs—and improves—decision making for both data science and the business.
How Facet Works
Facet delivers insights on the workings of AI in two ways:




The Benefits of Understanding Complex ML Models
Trust in AI
Focused Efforts
Responsible AI
Our Client’s Success with Facet
Meet Our Facet Team

Our Insights on Understanding Complex ML Models

