EyeSee has spent years developing a successful AI-powered packaging research solution. Now, as we move toward making more of that experience genuinely DIY, we are confronting a different set of questions: What can safely be handed over to users? Where do guardrails matter most? And how do you simplify research without oversimplifying the decisions behind it?
In this session, Jovana Sikanja will share what EyeSee is learning while evolving PackSee.AI toward a more self-service model. Rather than presenting DIY as simply faster or cheaper research, the session will explore the practical trade-offs involved in making sophisticated research easier to run independently, while protecting the rigor, context and interpretation that make the outputs useful.
Key takeaways:
• Understand what makes a research solution genuinely suitable for DIY.
• Recognize the most common risks when expert-led workflows become self-service.
• Learn where automation and guardrails can replace complexity without weakening methodology.
• See how EyeSee is evolving PackSee.AI from an expert-supported solution toward a more DIY experience.
• Identify when DIY research is enough and when expert involvement still adds value.
