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Our core technologies have been created from the ground-up to simultaneously deliver interpretability and state-of-the-art performance. Our focus on interpretability means: • Our technologies are effective and readily usable in applications that require interpretability (e.g. banking regulations on fair lending). • Model creation is transparent and easy to debug, resulting in a more efficient development process and a shorter time to impact. • Machine learning and AI solutions can be easily explained and understood by all stakeholders – from data scientists to executives – making them easy to deploy with confidence and effect change.

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Jack Dunn is the Co-Founder of Interpretable AI.

1 people are employed at Interpretable AI.

Interpretable AI is based in Cambridge, Massachusetts.

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