At Arturo, our team is constantly seeking partnerships with the most cutting edge providers across technology, data, and imagery to deliver the best property analytics to Insurance Carriers. We utilize multi-source imagery to enhance our process and push the boundaries on what we offer clients. …

As companies grow from start-ups to scale-ups, a wave of change is felt throughout the organization. At this transitional point, you most likely have aggressive revenue targets. …

Insurance carriers recognize the importance of imagery as a crucial input to meet their data requirements. However, determining the best imagery to use and how to integrate it into their systems and internal workflows can be very challenging. Insurance companies typically operate using annual or quarterly imagery, which can limit…

When the COVID pandemic first hit the United States, many companies had to quickly adjust to full-time remote workplace environments. Leadership and People teams scrambled to figure out the best way to enable productivity, motivate employees, and boost morale during uncertain times. …

Recently, I had the chance to sit down with Rob and Lee at the InsureTech Podcast. It turned out to be three, relatively nerdy-tech guys, talking about data science and applied machine learning. …

Here at Arturo.ai we are big supporters of the Open Source Software (OSS) community. While I currently serve as Chief Technology Officer of Arturo, I am proud to have financially supported a number of OSS efforts during my previous role at the National Geospatial-Intelligence Agency (NGA). Additionally, I had the…

In this series of engineering-focused blog posts, members of Arturo’s engineering team will dissect the infrastructure backing Arturo’s on-demand property analytics API. For this first post, I’ll discuss the three types of services that compose our service graph: Machine Learning (ML) Models, 3rd-Party Data Providers, and Feature Aggregators. Layers of…

Introduction Business decisions depend more on data than ever before, yet there is no way to know the reliability of each data point used in a decision. The best option for determining the reliability of data is to validate a subset of a data source against some (often arduously) collected ground…

The saying goes, “It takes a village to raise a child,” meaning that it takes an entire community interacting with a child for that child to safely/healthily grow and succeed in the community. Suppose if you will that roughly the same is true of the AI/ML community and the resulting…