XAI & Interpretability
XAI consultation for your team.
Machine learning models are black-boxes, meaning it's not clear exactly how they work under the hood. They do not reveal why they produce. XAI provides techniques to help developers and model practitioners understand why a machine learning model produces the outputs it does. With this, you can have confidence and trust in your models to be resilient and trustworthy. Our methods also allow you to reverse engineer potential model failures, allowing you to plan for the future and minimize any potential downtime. We can also help you train state-of-the-art “glass-box” architectures - deep learning models which are interpretable by design!
XAI: Bring Your Own Model (BYOM)
With our advanced post-training strategies, we can help you understand the inner-workings of your existing model to maximize your product’s potential. We also provide pre-training strategies to help you develop the most transparent machine learning model, allowing you to future proof your machine learning for years to come.
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