Mosaic Data Science’s supply chain optimization solutions are designed to streamline operations, from sourcing and production to distribution and delivery. Our team has ample experience helping customers minimize costs, reduce delays, and enhance overall performance.
Mosaic built an automated cooking prediction & optimizer using deep reinforcement learning to improve short term cooking operations.
Weather has a high impact on operations in many industries, and therefore is of great value to integrate into strategic decision making. Mosaic has roots in aviation research & development, giving us deep expertise in combining weather data streams with planning applications to facilitate efficient resource allocation.
Global external shocks are going to continue to happen, that is a fact of operating a business in today’s environment. As companies embrace data science in their decision-making processes, they are better positioned to deal with these disruptions, allowing them to manage a risk-optimized supply chain.
A leading CPG company wanted to diagnose cannibalization hypotheses using a data-analytics-driven approach.
In our white paper, Mosaic examines fresh machine learning based approaches to more accurately forecast airline seat demand.
Mosaic helps a leading 3PL company apply machine learning to predict brokerage profit drivers.
Mosaic was engaged by a leading hotel chain to assess the best way to predict future demand for hotel rooms across their various properties.
We designed and deployed an AI model to predict shipments at risk of late fees for one of the world’s largest CPG businesses.
We built a custom AI-driven tool for one of the largest Oil & Gas firms in the world to identify fuel usage anomalies across their entire fleet.
We revamped this trucking operator’s demand forecasting models to optimize fleet placement across North America.