explainable ai

There’s No Black Box Here

Mysterious black box AI? That’s so 2010.

We use cutting-edge tech that makes AI simple and explainable without skimping on robustness or power.

If you want to know why your AI came to the conclusions that guide your business decisions, then BigSquid.ai is for you. Instead of a black box, we think of our AI more like a gift box.

We want you to open that baby up like it’s your birthday and take a peek inside. Spoiler: it’s a chance to see the future (and play with it too.)

AI You Can Trust

What’s driving your success? If you want to know how your AI used your data to get from point A to point B, then Kraken is for you. When you’re using AI to guide your business decisions, we think you deserve to know the whys. Not only that, we make it so straightforward that not only will you know why, but you can easily tell your boss why, or your stakeholders, or even Jan in HR.

Kraken AutoML Explains the Results of Machine Learning Models With…

Exposure of All Algorithms

Kraken AutoML explores hundreds of models automatically to find the best performing model for your dataset. And we’ll show you every single one that was explored.

Performance Metrics

With the click of a button, you’ll see model results from hundreds of approaches, and we’ll even show you how they perform. In Model Metrics, we expose all of the relevant data science and statistical metrics to show you exactly how a model performs. If AUC, F1, Recall, Precision, Accuracy, R-squared, and RMSE are in your vocabulary, we have you covered.

Feature Importance (Driver Influence)

Drive Influence (a.k.a. feature importance) is a measure of how important a feature is to the overall prediction of a model. Know exactly what the most influential attributes in your data are to the outcome you’re predicting. Ever wonder what the most important factor is for lead conversion? We have your answer.

Full Feature Explainability

Predictive Influencers use Shapley values for every feature in your model to provide row-level explainability of how the model made its prediction, making it simple to interpret, explain, and share your model results with stakeholders.

90% of Kraken users build and deploy their own machine learning model within 30 days of signup.

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