Mosaic designs and deploys custom AI & ML solutions for a range of professional services firms; whether your specialty is management consulting, accounting, financial, or technical services, Mosaic can help your company make data-driven decisions.
Financial institutions are drowning in data. Traditional search tools struggle to keep up, hindering efficiency and crucial decision-making. Mosaic’s Neural Search Solution, powered by NextGen AI for financial services, tackles this challenge head-on.
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.
AI and LLMs are not just a technological leap; they’re a strategic imperative. By embracing this evolution, businesses gain a distinct advantage—staying ahead of the competition, enhancing stakeholder experiences, and optimizing both time and costs. In this white paper, we explore our top LLM business applications.
Mosaic Data Science and Epstein Baker Green discuss the importance of developing ethical algorithms that comply with anti-discrimination laws.
Mosaic helped one of the US’s largest regional homebuilders deploy an artificial intelligence engine that recommends the optimal community features based on different geographic regions. The recommender delivers data-driven insights the company can trust when planning, building, and positioning new communities.
Mosaic supports Epstein Becker Green by deploying AI to support the law firm’s algorithmic bias auditing & risk management services.
Both descriptive analytics and machine learning models can benefit greatly from using geographic data analysis to solve segmentation use cases.
As our world becomes more and more digitized, organizations need to leverage behavior data to provide a better customer experience and detect potential problems before they arise. This can be achieved by analyzing behavior patterns from digital platforms customers operate.
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.
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.