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.
See our AI/ML deployments in action through our detailed case studies. Explore a curated selection of real-world scenarios, each meticulously dissected to showcase the transformative power of AI and machine learning. Delve into the strategies that drive efficiency, unearth hidden opportunities, and illuminate the path to informed decision-making. As you navigate through our case studies, you’ll witness firsthand how Mosaic Data Science translates data into actionable insights, propelling businesses into a future of success.
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.
Mosaic has been working with a leading pet Biotech company on integrating machine learning into the organization’s products, giving pet owners more visibility into the quality of life their pets have by identifying genetic traits that may impact their health or behavior.
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.
Mosaic built a computer vision solution to improve the process of a vehicle moving through an automated car wash.
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.
Advanced analytical techniques help manufacturers reduce inventory levels of parts required in manufacturing activities while maintaining confidence that they will not run out of parts. Mosaic was tapped to help a manufacturing company in the semiconductor industry solve the complex problem of optimizing their inventory for both future orders and historical demand rates
Summary Mosaic helped an energy company optimize its hydrocarbon inventory management process by working with them to develop a centralized system to collect and control inventory data quality, improve accuracy, and improve the bottom line. Why Intelligent Inventory Management Matters in the Oil & Gas Sector The oil and gas Read more…
The business was investigating how to incorporate modern data science techniques into their budgeting decisions. Since they didn’t have this expertise in-house, they needed an analytics partner that could provide the right capabilities to accurately model and forecast revenue and serve these results to users in the proper context.
Mosaic helped a leading hospital optimize the scheduling of elective surgery and created a better daily rhythm for surgeons.