Data science & Engineering
Half day
350
Mechelen
With a pilot launch planned in just one month, our client wanted to ensure a Q&A chatbot was safe, compliant, and reliable. Enter our AI Risk Assessment Workshop, a collaborative session led by our Responsible AI experts to identify and mitigate risks. In this post, we’ll walk you through how we addressed the client's challenges and why this process is critical for responsible AI deployment.
Your data isn’t lacking infrastructure. It’s lacking impact.
Product thinking brings the focus back to business outcomes—by treating data like a product, not a project.
Blood platelets present a unique healthcare supply chain challenge with their critical importance and extremely short shelf life. By precisely forecasting platelet demand, healthcare providers can better balance patient needs with resource optimization, resulting in reduced waste, significant cost savings, and more reliable care. This case study explores how advanced analytics transforms healthcare logistics while maximizing the impact of every blood donation.
AI applications have taken off across industries. From chatbots generating creative content to AI-driven automation in finance and customer service, businesses are seeing real impact. But as AI adoption grows, so do the challenges—bias in decision-making, transparency concerns, and even security risks like deepfake fraud. How can organizations ensure AI delivers value while staying responsible?
