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
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 market 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.
Filtering search results is an essential part of any eCommerce website. Can you remember the last time you shopped online without filtering on product attributes such as color, size, brand, etc. Additionally, rich product attributes are critical to Google SEO which drives traffic and website sales.
Mosaic developed a data-driven alerting solution powered by unsupervised learning to assist a leading energy utility in detecting voltage anomalies & informing optimal grid health decisions.
Mosaic developed an innovative optimization app for the green power sales function at a leading utility, helping them recommend suites of renewable energy products to meet corporate carbon footprint reduction goals within budgetary constraints.
Mosaic designed and deployed custom computer vision models to automate asset recognition & inform inspection decisions.
Mosaic designed and deployed a custom machine learning model to help this retail energy company predict customer churn and inform a geographic growth strategy.