Case Study

Investment firm achieves breakthrough efficiency: 65% faster analytics with UST Xpresso

The IT team wanted to simplify its complex analytics application footprint. After deploying UST Xpresso, the company standardized its data science tools and transformed its approach to analytics. The “game-changer” MLOps platform accelerated analytics by 65%, enabling the data science team to play a more consultative role in asset management.


This European multinational company provides investment management solutions to clients worldwide. With more than £200 billion in assets under management, it employs nearly 1,000 people.


Maintaining a diverse analytics environment

The data scientists at this investment company analyze historical asset performance data, market trends, and other key investment factors to help asset managers make data-driven decisions to optimize investment strategies and asset portfolios. Each data scientist used the analytics tools they liked best. The different applications were complex and challenging for the IT team to maintain. The company wanted to implement a standardized analytics infrastructure that would be easier to manage and provide the highly skilled data scientists with robust tools to streamline and accelerate their work.


UST Xpresso MLOps platform consolidated and streamlined analytics capabilities

After conducting a thorough analysis of the existing IT environment and analytics tools as well as the needs of the data scientists, UST Xpresso was deployed. Its machine learning operations (MLOps) platform enabled the analytics team to build, train, and deploy AI, ML, and large language models (LLMs) efficiently at scale. The solution was designed so the data scientists can easily:

Now, the data science team can automatically pull and merge data from various in-house and external data sources, create and test data pipelines on the IT infrastructure of their choice, and easily deploy ML models into production.

Since the solution was deployed as a managed service, the company’s IT team doesn’t have to maintain the application or underlying infrastructure, allowing the team to focus on more strategic projects. The data scientists and IT personnel can contact the UST Xpresso team for help whenever necessary. In a recent support effort, the UST Xpresso team helped the company provision new hardware in just a few days, saving the IT team weeks of work.


Data science team achieved 65% faster development and resource efficiency

Because the data scientists have all of the analytics tools they need in a single solution, the team has accelerated development timeframes and reduced required resources by 65%—thanks to the modular, reusable development components, the centralized code repository, standardized tracking, monitoring, debugging, and deployment processes, and built-in audit reporting.

The new streamlined MLOps platform has also enabled the data science team to take a consultancy approach to analytics by creating a pipeline development roadmap that aligns with the investment firm’s strategic business goals.

A senior program manager at the investment company stated, “The impressive results that UST has achieved are game-changing. We have created a common investment language to inform the investment decision-making process. We are no longer debating the number or the method, but rather how we act on that number.”