SciSure Talks: Safe AI for Science

In many labs, data is still fragmented across multiple systems, making it difficult for AI to access the context it needs without manual effort. As a result, much of today’s AI remains disconnected from everyday scientific work.

At the same time, adopting AI in research raises important questions around data security, IP protection, and responsible use. How can labs innovate with AI while maintaining control and compliance?

In this session, we’ll explore how to close that gap and unlock meaningful value from AI in lab environments.
You can expect:

• Practical perspectives on connecting AI to scientific data and workflows
• Real-world examples of how this shift can improve efficiency and discovery
• Discussion on how to approach AI adoption while addressing security, IP, and governance concerns

A quick note: the event will be held in English.
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Info: During this talk, we’ll explore how AI in labs is moving beyond isolated tools into connected systems that interact directly with scientific data. We’ll show how technologies like MCP are unlocking faster insights, smarter workflows, and more meaningful discoveries.

Info: In this presentation, we plan to cover how cybernetic principles apply to modern labs and their digital transformation. Focusing on the interplay of architecture, execution, and interaction, we’ll show how system design shapes data flow, behaviour, and outcomes across software, AI, and organizations, and how these principles can be applied to build more structured, scalable, and effective lab environments.

Info: An interactive workshop designed to help you identify what would make the biggest difference in your AI journey. By combining your perspective with insights from others, this session will help you reflect on how these insights apply to your own work, whether you’re just starting out or looking to scale AI within your lab or organization.

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