Experimentation is easy. Real-world deployment? That’s where the infrastructure proves its worth.

In this session, we’ll go beyond prototypes and pilot programs to explore what it really takes to build AI infrastructure that holds up under production demands. From GPU scheduling and model orchestration to observability, governance, and scaling compute across hybrid environments—this discussion is for teams ready to move past the lab and into sustained delivery.

Our panel of leaders will break down architectural trade-offs, emerging best practices, and the organizational realities of supporting production-grade AI.

What You'll Learn:

1️⃣ Foundational Stack Components: What your AI infrastructure needs to support scale, speed, and stability in production.

2️⃣ Deployment Realities: Insights into latency, availability, compliance, and lifecycle management when shipping AI to production.

3️⃣Infrastructure as Collaboration: How infra, ML, and product teams can align on goals, budgets, and tooling without bottlenecks.Engage live with founders and builders shaping the future of autonomous enterprise solutions.

Panelists to be announced soon.

Register here