Mosaic Data Science offers manufacturing machine learning consulting to help firms run high-velocity data streams through world-class, custom-built predictive models. We partner with your business to make sure you are well-positioned to take advantage of the wealth of insights provided by mechanical, human, and market data.
In this case study, Mosaic fine-tuned language models to analyze text and quantify public sentiment to explain commodity pricing with AI. Our team used sentiment model outputs to extract insights regarding price trends for a specific commodity and predict future price movements.
Using AI to analyze sensor data, Mosaic helped a renewable energy producer optimize furnace temperature to improve wood pellet production efficiency by reducing slag production and pressure buildup and providing control room operators with easy-to-use recommendations for setting furnace controls.
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
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.
Summary Our white paper explores the processes and opportunities presented by NLP for social media in extracting valuable data to drive improved operational and strategic decisions for R&D efforts. Natural language processing (NLP) is one of the most promising social media data processing avenues. It is a scientific challenge to Read more
We explore how ML & optimization can aid the risk assessment and management process with an eye towards robustness and resiliency.
Mosaic built a computer vision solution to improve the process of a vehicle moving through an automated car wash.
Wielding the power of computer vision human action extraction to gain insights from video data presents an opportunity for logistics companies to make improvements for new and current customers.
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