Summary Our white paper explores the processes and opportunities presented by NLP for social media in extracting valuable data to drive improved operational and strategic decisions for R&D efforts. Natural language processing (NLP) is one of the most promising social media data processing avenues. It is a scientific challenge to Read more…
We explore how ML & optimization can aid the risk assessment and management process with an eye towards robustness and resiliency.
Both descriptive analytics and machine learning models can benefit greatly from using geographic data analysis to solve segmentation use cases.
Mosaic helped a trucking and logistics operator optimize their machine learning deployment on Amazon Web Services (AWS). As an AWS Select Partner, Mosaic was well-positioned to deploy machine learning engineering and serverless architecture services that sped up model inference while performing a minor overhaul of the AWS architecture and code base organization.
Wielding the power of computer vision human action extraction to gain insights from video data presents an opportunity for logistics companies to make improvements for new and current customers.
As our world becomes more and more digitized, organizations need to leverage behavior data to provide a better customer experience and detect potential problems before they arise. This can be achieved by analyzing behavior patterns from digital platforms customers operate.
Contextual search can be labeled as a search capability that focuses on the context of the user-generated query including the original intent of the user to show the most relevant set of results. It is quite different than traditional search technologies which focus only on keyword matching.
Fantasy sports represent a rich and exciting world of modeling and analytic possibilities. With the advent of modern computer vision, statistics tracking, and the general embrace of the sporting community of a “data-centric” view to the game, there is a wealth of information available about each player, their performances, and various metadata.
Mosaic used NLP algorithms to automatically extract various insights about people calling into a customer call center. We created a process to identify at-risk customers that called the previous day based on the transcript of the call.