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Case studies

Insurances

How we built a personalized health recommendation engine

For a client in the health insurance domain, a health recommendation engine is crucial. We integrated this engine, after the design and development phase, on top of an existing health trajectory prediction application. Our goal was to ensure the client could offer recommendations on treatment and disease prevention by lowering their potential risk.

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Finance

How we crawled company data from the web

With only the company name available, how would you learn more about a given business—or even gather leads to get in touch with that business? We were approached by a client to build a comprehensive database not only covering certain companies’ individual characteristics, but also extending their data with information from unstructured sources in the WWW. Using cloud technologies and web-scraping frameworks, we built a data-mart that provided an extensive overview of different companies.

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Industry 4.0

How we introduced predictive maintenance in the mining industry

For a client in the mining industry, we developed machine learning models that continuously predict the wear of a complex machine over the next days and weeks. The AI can learn which factors and machine conditions drive the highest wear, all while explaining how it came to certain predictions in a clear and concise way. Through this approach, we’ve not only managed to predict future wear (therefore enabling an optimized maintenance schedule), but we’ve also created optimal machine setting guidelines to reduce future wear.

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Insurances

How we extracted insights from unstructured PDF documents

For a client in the medical domain, we converted a significant amount of unstructured health records into structured insights. Challenges included navigating discrepancies involving how health records might look, and addressing the fact that relevant data can reside anywhere—in tables, as free text, or even in handwritten notes. Yet with our solution, the client can tap into a so-far-unused dataset and drive novel use cases.

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Industry 4.0

How we used clustering to strengthen machine understanding

For a client in the mining industry, we developed machine learning models that understand and learn machine states and behaviors without human intervention. In a data explorer tool, these states and behaviors were visualized in a way that enabled discussion with subject matter experts, with the goal of deriving optimized machine configurations.

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Insurances

How we leveraged pet insurance data to predict diseases

For a client in the insurance industry, data is essential. This is where SPRYFOX’s machine learning models come in. Using our engine, the client can get a better sense of pets’ health trajectories. Our models allow insurance experts to predict their furry customers’ likelihood of contracting specific conditions, providing vital insights that can help pets live longer, healthier lives.

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