AI and Data Science Consulting
for 7 and 8-Figure Businesses

We use AI, machine learning, and data science to help you …

… get more customers
… increase sales
… get the insights you need to grow your business

What We Do

Data Strategy

Most companies struggle to use their data effectively, because they don’t know what to do.

We’ll work with you to understand your business goals, identify what data capabilities can help you meet those goals, and then develop a data strategy for your business to bridge the gap.

Prototyping and Staff Augmentation

Once you know what data capabilities you need, we can help you fill in any gaps in your business buy helping you build data deliverables and systems.

This includes helping you with reporting, analytics, dashboarding, building machine learning systems, and more.


Although we can directly help you build data deliverables and systems, ideally, you should try to build teams of people inside your business that can do data science work.

We can help you train your employees in all of the essentials of data science, including data wrangling, visualization, analytics, machine learning, and more.

An image of Amazon stock price, visualized as a line chart.
An image of the counties in the United States, colored according to unemployment rate.

– Sharon P. (Sharp Sight Student)

Recent Blog Posts

Machine Learning Regularization, Explained

Machine Learning Regularization, Explained

Dealing with the problem of overfitting is one of the core issues in machine learning and AI. Your model seems to work perfectly on the training set, but when you try to validate it on the test set … it’s terrible. This is a core problem in machine...

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Machine Learning Hyperparameters, Explained

Machine Learning Hyperparameters, Explained

If you want to build high-performing machine learning and AI systems, then simply training those systems is rarely enough. You often need to build multiple models, often with multiple different algorithms, and then compare the different models to each other to see...

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Cross Validation, Explained

Cross Validation, Explained

In machine learning, making sure that you have a model that performs well is, in some sense, the most important thing. This means that you need to be really good at evaluating different models. But, this can be a challenge, as you run into issues like overfitting,...

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