The choice of Google Cloud doesn't just support high-level strategic goals; its benefits are also seen daily in the reduced workload for the company's teams. "Google Cloud allows us to automate a large part of our operations, which lets us maintain and secure the platform with a very lean DevOps team. The difference is clear compared to non-Google Cloud environments we see at some clients, where the operational burden is much heavier. As a result, we can dedicate more time to evolving our offering," adds Sébastien Vigue.

The benefits also translate into tangible competitive advantages for Yields' clients, especially financial institutions that require strong guarantees of security, resilience, and data localization. Thanks to Google Cloud's global data center presence, the Yields platform can be deployed close to regulatory constraints, simplifying compliance management and accelerating project implementation. This proximity, combined with the robustness of the infrastructure, strengthens client trust and significantly reduces the time needed to bring new features into production.

With these operational advantages and a proven infrastructure, Yields took a new step in 2024. The company added AI model governance to its solutions portfolio, anticipating the technological and regulatory challenges associated with enterprise AI adoption. This strategic expansion addresses a dual market dynamic. On one hand, the rapid adoption of AI technologies by companies creates a growing dependency on models and a need for operational tools to manage their risks. On the other, the regulatory framework is becoming clearer, particularly in Europe, where the EU AI Act is imposing new standards for documentation, risk management, and auditability.

"AI governance is becoming essential for all companies. With our expertise in model risk management , we are ideally placed to offer solutions tailored to this new need, especially since Google Cloud provides us with the reliability and scalability required to do it on a large scale," highlights Helena Goyvaerts, Head of Partnerships at Yields.

To make its offering clearer and support this evolution, Yields recently restructured its platform around two essential capabilities. "Our mission is to simplify model governance by turning it into a repeatable operational practice," explains Sébastien Vigué. "This new structure reflects that ambition: Yields enables organizations to both test and validate model performance and ensure transparency and regulatory compliance, two dimensions that are critical for trustworthy AI."

This transformation was facilitated by the Google Cloud ecosystem. Thanks to the power of GKE, which automatically handles orchestration, Yields was able to recombine, evolve, and add new components to its platform with minimal effort. Furthermore, the implementation of the 'Performance module' was made easier by solutions like BigQuery, which allows for large-scale quantitative tests, while the Governance module relies on services like Cloud KMS, which provides security guarantees and protection for sensitive information.

Beyond clarifying the offering, this restructuring also prepares the platform for new challenges related to generative AI. With the rise of large language models, companies need specific control, documentation, and evaluation mechanisms. Yields has therefore enriched its solution with features adapted to these uses, with calculations running directly on Google Cloud. The platform also offers an integrated AI assistant that each client can connect to the LLM environment of their choice, including Gemini.