Contextual Search Engine Development

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.

By Sel Gerosa, ago

Advanced Industrial Inventory Management Analytics

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

By Sel Gerosa, ago

Intelligent Hydrocarbon Inventory Management

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

By Sel Gerosa, ago

Summarizing Text with Artificial Intelligence

Text data presents a tremendous opportunity to benefit all stakeholders of an organization – investors, employees, processes, and the all-important customer – if the organization can find a way to sift through this data in an automated way to extract key information and solve specific challenges. In that case, they could learn about their firm and start optimizing the way they operate.

By Sel Gerosa, ago

Transformation: AI

Mosaic sees Digital Transformation differently; our view is that while the technology is a critical part of any Digital Transformation, it’s only a part of a greater whole that includes people, process, and culture change that all combine to enable effective use of the technology.

By Sel Gerosa, ago

Integrated Machine Learning and Mathematical Optimization

For the past several years, ML has exploded in popularity, while the excitement for MO has mostly plateaued. Why this has occurred is very much up for debate. One might surmise that ML is simply a better tool than MO, and therefore it replaced it in terms of popularity. This, however, is wrong-headed. ML and MO are typically used to solve very different problems. One might also think that problems MO has historically solved no longer exist.

By Sel Gerosa, ago
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