The Opportunity
The department had grown quickly, but without a shared framework. Each team had its own stack, conventions, and shortcuts, which made it hard to reuse work, onboard new projects, or guarantee reliability at scale.
Siloed teams
Data teams operated in silos, each with their own structure, technologies, and custom tweaks that accumulated technical debt and made collaboration difficult.
Lack of scalable systems
There was no framework in place to build reliable, uniform, and reproducible pipelines at scale. Every new project meant re-solving the same infrastructure and orchestration problems.
Slow time-to-market
Delivery cycles were far longer than the business expected, limiting investment and reducing confidence in the department’s ability to deliver impact.
The Solution
LUPA - Lightweight Universal Profiles Accelerator - is an MLOps platform designed to support both data scientists and data engineers. It manages the necessary infrastructure and implements a unified framework for building, deploying, and monitoring data and ML pipelines, helping eliminate hidden technical debt and shorten time-to-market.
LUPA was built with a market-oriented mindset, empowering data teams to take ownership of their products rather than relying on ad-hoc support. At its core, it uses open-source components such as Spark, Airflow, Soda, and MLflow, and its agnostic design allows other open-source tools to be adopted as needed.
A cloud version, CLUPA, integrates with Google Cloud Platform through Terraform, enabling developers to set up infrastructure in just two days. This makes it easier to spin up new environments, standardize configurations, and keep infrastructure changes under control.
The Impact
LUPA has become the backbone of the advanced analytics department, serving as the foundation for more than 20 data science projects and involving over 80 developers - an adoption rate of around 80%. Onboarding new projects now takes just two days thanks to the platform’s standardized framework.
Business owners are experiencing a new reality: time-to-market has decreased by approximately 75%. This encourages them to iterate on existing projects and explore new business opportunities, rather than being constrained by lengthy timelines.
Beyond reducing time-to-market, LUPA supports large-scale projects that represent multi-million-euro impact on the company’s revenue. For example, it powers the company’s recommendation system that selects personalized offers for up to 1.5 million clients, running on top of the same shared MLOps foundation.
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