Building trustworthy AI systems

AI based proofs of concept are popping up everywhere. But taking an AI solution from prototype to production is about more than just solving technical challenges—it's about earning trust.

AI systems are often perceived as complex black boxes, which can make it difficult for users to fully understand or feel confident relying on them. In this edition of AI Talks, we explore what it takes to build AI systems that people actually want to rely on, covering topics such as adoption, evaluation, and uncertainty estimation.

📅 Date: May 21st, 2025
🕕 Time: 6:00 PM onwards with a drink (we'll start at 6.30 PM)
📍 Location: Cantersteen 47, Central Gate, 1000 Brussels

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Important: To attend, please make sure to fill out the registration form.
Completing this form is necessary to secure your spot at the event!
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Get ready for these insightful talks:

🎤 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐧𝐠 𝐋𝐋𝐌-𝐛𝐚𝐬𝐞𝐝 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 – 𝐅𝐫𝐨𝐦 𝐏𝐫𝐢𝐧𝐜𝐢𝐩𝐥𝐞𝐬 𝐭𝐨 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞

LLMs can unlock powerful workflows, but how do you know if they’re actually working and don’t regress over time? In this talk, we break down the core principles of LLM app evaluation, from building test sets and choosing the right metrics to structuring a full evaluation pipeline. Then we zoom into a real-world use case at Exalate, showing how we evaluate our assistant during development and monitor it in production. Whether you’re building your first LLM app or scaling one in production, this session offers practical advice for making evaluation part of your process.

By Usman Shani (AI Engineer at Exalate) and Stijn Goossens (Solution Architect at Superlinear)

🎤 𝐅𝐫𝐨𝐦 𝐏𝐢𝐱𝐞𝐥𝐬 𝐭𝐨 𝐈𝐦𝐩𝐚𝐜𝐭 – 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐧𝐠 𝐂𝐚𝐫 𝐃𝐚𝐦𝐚𝐠𝐞 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐕𝐢𝐬𝐢𝐨𝐧 𝐀𝐈

Macadam inspects thousands of vehicles every day. Ensuring consistency, speed, and accuracy across inspections is a massive operational challenge. In this session, we share how we used computer vision to automatically detect damages—turning a manual process into an AI supported workflow. We’ll walk through how we co-designed the solution with users in the loop and what it took to build trust in the application throughout the organization as we moved from prototype to production.

By Dieter Maes (Product Owner at Macadam) and Mathieu Kitenge (Machine Learning Engineer at Superlinear)

🎤 𝐓𝐚𝐦𝐢𝐧𝐠 𝐮𝐧𝐜𝐞𝐫𝐭𝐚𝐢𝐧𝐭𝐲 𝐰𝐢𝐭𝐡 𝐜𝐨𝐧𝐟𝐨𝐫𝐦𝐚𝐥 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧

Machine learning is increasingly used in high-stakes decision making—from predicting electricity demand and stocking shelves to diagnosing medical conditions. But how do we know whether to trust an AI’s prediction? In this talk, we’ll introduce conformal prediction, a powerful method for quantifying uncertainty, and show how the open-source package, Conformal Tights, lets you move beyond point predictions to generate reliable prediction intervals that guide better, safer decisions.

By Jan Wuzyk (Solution Architect at Superlinear)

Why join us?
At the AI Talks by Superlinear, you’ll…

• Network with top AI professionals from Belgium
• Dive into practical AI applications shaping industries
• Enjoy great finger food, drinks, and inspiring conversations

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Interested to attend?
Be sure to fill out the registration form on the event page to secure your spot!