Many customers and prospects have told us they have projects they’d like to start immediately, but they are short-staffed, or their data scientists lack the relevant ML expertise to undertake a new initiative. In response to this market demand, Mosaic offers a staff augmentation model to meet our clients’ machine learning & analytics needs. Mosaic can rent your company a data scientist (or two) with the optimal skillset for your project at a competitive hourly rate, on a part-time or full-time basis, for as long as your project requires.
Mosaic helped a North American provider of international freight forwarding services build an NLP solution that automates the tariff classification process, saving valuable resources and reducing risk while improving the customer experience.
Mosaic helped a commercial airline integrate custom machine learning to predict departure runway and taxi-out time, cut operational costs, and improve the customer experience, aiding in reducing fuel emissions with AI.
Mosaic built a custom voice search solution using deep learning and state-of-the-art language models to intelligently parse complex mechanical operation manuals and return the desired search results
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.
Mosaic used NLP algorithms to automatically extract various insights about people calling into a customer call center. We created a process to identify at-risk customers that called the previous day based on the transcript of the call.
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