Our expertise

(Generative) AI

Generative AI (GenAI) is an advanced form of Artificial Intelligence capable of creating new data by learning from existing information much faster and more accurately than any human could. It feels like having a crystal ball that reveals the future based on present and historical data.

GenAI leverages the value embedded in your data. It has the capability to identify patterns and anomalies that can support decision making by people. This is how GenAI releases and enhances the value of your data.

What we believe

But just because we can use AI, does not always mean we should. Understanding how AI models work, what and how they use the data, and the constraints they operate under is a prerequisite for using AI solutions. Especially GenAI.

Adoption is dependent on the level of trust people can have. Therefore, this must be baked into the design process of AI use cases.

Our six (Gen) AI design principles

To mitigate risks and bolster trust, we live by our (Gen)AI Manifesto.

This is a comprehensive set of design principles that ensure we keep ethics and trustworthiness top of mind when developing AI solutions. The six principles are:

Embedded legal compliance

We handle data in accordance with legislation such as GDPR and the EU AI Act. We clearly identify associated risks and take the necessary measures to ensure our AI solutions are safe, ethical, transparent, and compliant with the EU AI Act and other specific legislation such as the Machinery Directive.

Transparency and traceability

We create clarity about how models are trained and used. We train people in GenAI risks and safeguards.

Our developers are the epitome of awareness and help others grow their understanding of GenAI and the boundaries and risks embedded in their data.

We help users understand how a model generates decisions. These decisions must be easy to understand and auditable.

Fairness and equity

We embed fairness, privacy, and safety into our designs. Limiting bias in AI outputs is a priority for all use cases. We ensure fairness and equity in outputs, by eliminating bias in the data that we use.

Responsible

Our solutions are developed in a socially responsible and sustainable way. We prevent risks of physical or digital harm and consider the energy use of AI. We use our CO2 calculator to assess use cases and choose more sustainable configurations.

Accountable

We define who is accountable for AI outputs of use cases. Policies are in place to determine who is accountable for the decisions made with our AI solutions.

Resilient and secure

We build solutions that are resilient against outside influences and have security built-in as much as possible. We use our AI best practices, as we believe this prevents us from making unnecessary mistakes.

How we work

Our AI Center of Innovation significantly speeds up the implementation of AI solutions. Embedded in your day-to-day operations, these solutions leverage the value in your data and boost the quality of decisions by your people. Our UX engineers are experts in designing interfaces that make human interaction with AI solutions very intuitive, supporting their adoption.

We have developed best practices to ascertain a focus on ethics and trustworthiness of the AI solutions we develop, and to prevent problems such as hallucination and bias. They cover people, process and technology aspects of developing and managing AI solutions.

This is how we embed enterprise-grade AI solutions in a controlled way.

Whether you don’t know where to start, lack the experience, or struggle to find the right use case, we can assist you in defining the feasibility of (Gen)AI use cases in 5-7 weeks.

Together, we explore, design, validate, and build a demonstrator that makes a use case tangible and supports a business decision to implement it.

When you are happy with the demonstrator and feel confident the value can indeed be realized, we are eager to assist you with its professional implementation in a controlled way.