Case Studies
Maximizing Revenue With Machine Learning for Retail Pricing
Mosaic helped a nationwide retailer model the price elasticity of demand across their product catalog, empowering them to optimize prices and maximize SKU revenue.
Whether you want to do some exploratory data science work to investigate a business case or deploy custom intelligent apps into production environments, Mosaic is ready to help. We strive for excellent project outcomes, iterating with our customers throughout the ML & AI life-cycle.
Mosaic is comfortable managing and executing projects, supporting an existing project team, serving as an outside advisor, or filling any other role that meets your project’s needs.
Mosaic helped a nationwide retailer model the price elasticity of demand across their product catalog, empowering them to optimize prices and maximize SKU revenue.
Mosaic worked with a vet tech company to develop an encompassing pet wellness score and early disease-identification models using an AI-driven collar device that collects pet behavioral information and reports health insights to the owner’s app using IoT and sensor data techniques.
Graph analytics is a classic network science technique that is making waves due to the advancements in Graph Database Technology (GDB) and the integration of machine learning techniques (i.e., neural networks), to solve a wide range of use cases. No need for a map to figure this one out – Principal Data Scientist, Daniel Salazar is giving us the full scoop as our guide.
We scheduled some time for this Q&A with Principal Data Scientist Evan Lynch, where we explored the many cross-industry challenges that scheduling optimization aims to solve, and the robust scheduling techniques that lie at the junction between mathematical optimization and machine learning.
Given a set of nodes & connections, which can abstract anything from transportation networks, connections between customers, knowledge graphs, or molecular structures to computer data, graph analytics provide a helpful tool to quantify & simplify the many moving parts of dynamic systems.
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 was contracted by multi-national manufacturer of construction and mining equipment to develop a proof-of-concept predictive maintenance model to predict equipment failure before it happens to minimize downtime and optimize maintenance schedules.
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.