> We partner with industry professionals

Our Industry Experience

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    We work with you to understand your needs inside and out. For example, in developing an application for a customer, we spent a week with the baggage handlers to understand their needs and challenges. When we noticed that they typically wore gloves, which made it difficult to handle the mouse, we designed and developed a web-based app that could navigate through the keyboard.

> How we approach our clients problems

Design Thinking

It all starts with our team feeling your pain. We probe, explore and leverage our industry expertise to acutely understand your problem, document your specific requirements, and then use design thinking to arrive at a solution using that expertise, as well as creativity and systemic reasoning. Our software architects and business analysts then work together to deliver on that design, creating a solution that moves your business forward.


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Agile Software Development

What software development methodology do we use to build your solution?  Whichever one best meets your project’s needs. Our software development team is highly skilled in a variety of iterative and incremental software development methodologies, such as agile, yet we are just as versed in waterfall software development.


Continuous Improvements

Since technologies continue to evolve and your needs change as well,  we’re committed to maintaining and continuously improving your solution, making sure it continues to solve your problems, remain compatible with new devices, and that machine learning algorithms are retrained with the latest data. 


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  • The New Jobs in Hot Demand Thanks to AI

    I recently wrote an article for the Forbes Technology Council that described some of the new jobs that did not exist even a few years ago, but thanks to AI, are in growing demand. Against mounting stories on AI being the next big job killer, I was hoping to shed a hopeful light on the fact... Read more »

  • P-Hacking a Statistical Pitfall of Machine Learning

    A factor that can significantly affect a machine learning model’s performance is P-hacking. In broad terms, it refers to the incorrect usage of data that produces misleading statistical results. The P in P-hacking refers to the p-value, a measure of the statistical significance of an experiment’s results. In other words, P-hacking is the improvement of... Read more »

  • The Problems with Imbalanced Datasets and How to Solve Them

    In one of our latest posts my colleague David shared some valuable insights regarding predicting customer churn with deep learning for one of Wovenware’s healthcare clients. He mentioned that a key part of the business problem was working with an imbalanced dataset. This blog post is the second in a three-part series where I will share... Read more »