Platform Perspective: Building Secure AI Systems at Scale

Virtual event

Feb 19, 2026 6:00 PM

Register today

Key Takeaways

Architect secure AI infrastructure from day oneLearn how to design infrastructure that protects models, data pipelines, and inference endpoints by default, so security is part of the foundation rather than an afterthought.
Apply a frontier AI lab's security playbookSee how Cohere builds security into every layer of their platform and walk away with architectural patterns you can adapt for your own AI systems.
Scale AI systems without scaling riskDiscover which design decisions around identity, access control, and data isolation matter most when moving AI workloads from prototype to production at enterprise scale.

About this webinar:

This session gives you a platform-level view of what it takes to build secure AI systems that hold up at enterprise scale. You will hear how a frontier AI lab approaches infrastructure decisions, identity boundaries, and data protection as first-class concerns throughout the development lifecycle. Walk away with architectural patterns and practical guidance you can bring back to your own AI builds, including:

See how a leading AI lab designs security into infrastructure, identity, and data layers from the start
Learn which architectural decisions have the biggest impact on AI system security at scale
Get a clear framework for evaluating where your own AI builds need stronger security boundaries
Hear real examples of how platform-level security decisions prevent downstream risk

For those who are:

Security leaders and practitioners who are responsible for securing AI workloads in cloud environments.
Platform and infrastructure engineers who are building or scaling AI systems in production.
DevSecOps teams who need a practical blueprint for integrating security into AI development pipelines.