[Webinar] Components of Physical AI

Physical AI projects stall at the same place: the boundary between hardware, embedded software, and AI. Three separate teams, three separate specs, and a handoff that assumes the next team will figure it out.

In this webinar, we get into the Sense-Decide-Act loop and what it actually takes to design across the full stack. Where the integration breaks, why it breaks there, and what teams building Physical AI systems need to get right before it shows up as a production problem.

This is a practical discussion for engineering and product leaders who are building Physical AI systems and want a grounded look at the architecture decisions that determine whether a program ships.

See the full conversation.

What you'll learn: 

• How perception, edge inference, and physical action connect in deployed Physical AI systems
• Where the integration breaks between hardware, embedded, and AI teams and why it consistently happens at the same points
• How to build edge AI that makes decisions locally, without cloud dependency
• Why HMI is harder than most teams expect and when it becomes a program-level risk
• How to design across the full stack from the start rather than integrating at the end

This session is for technical leaders heading into a Physical AI build who want to pressure-test their architecture before it's too late to change it.

Speakers:

• Mahmood Afshari – Business Development Manager, Softeq Munich
• Chris Howard – Founder & CEO, Softeq

Ready to explore your use case?

Let's talk about how we can help you take your next Physical AI project from concept to production.