Mosaic Data Science’s optimization services leverage the latest advancements in artificial intelligence with traditional optimization techniques, such as mathematical optimization and scheduling optimization, to drive unparalleled efficiency and performance. Our expert team helps customers fine-tune processes, resources, and strategies through data-driven insights and predictive modeling. From supply chain streamlining to resource allocation, we harness the power of math to enhance decision-making and achieve optimal outcomes.
Decision processes in support of jobs that either cannot be or are very difficult to automate are frequently overlooked by out of the box software providers. One such process is the creation of optimal staffing plans for outbound teams loading cartons onto trucks.
Mosaic built an automated cooking prediction & optimizer using deep reinforcement learning to improve short term cooking operations.
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 clothing manufacturer distributor and retailer of clothing realized they needed to fortify their pricing decisions with machine learning insights.
Data Science, specifically machine learning forecasting techniques, enables decision makers across a spectrum of industries to set more effective sales targets and plan profitable customer routes that boost top and bottom line growth.
Optimizing seasonal staffing and resourcing is a key challenge for many industries, especially when the exact timing of high-volume activity can change based on complex factors.
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 helped one of the largest Children’s Healthcare Network more accurately forecast patient volume across their hospitals.
Retail inventory optimization is a great candidate use case to apply machine learning & deliver immediate business value.
Oil & gas firms have a tremendous opportunity to refresh demand forecasts with ML techniques, improving accuracy and adding to the bottom line.