Understand the architecture.
Map where AI enters your application, which data it can access and what actions surrounding components can perform.
Consulting / AI security
Build AI.
Think security.
Bring security into the decisions around your AI applications—from system design to deployment and everyday operation.
The model is part
of the system.
AI security starts with the whole application: its data, permissions, connected tools and the people who use it.
Review trust boundaries.
Discuss how input, retrieved content, generated output and tool access move across the system’s boundaries.
Shape implementation priorities.
Identify the security questions your team needs to resolve and agree on practical changes for your environment.
Before a launch.
Bring an architecture overview and the intended use case. We can discuss security considerations while design decisions are still flexible.
After deployment.
Bring the system’s current behavior, concerns and constraints. Start a focused conversation about what needs review or improvement.
A useful first conversation.
Share what the application does, the users it serves and the systems it connects to. Keep initial material high-level; any detailed review and handling of sensitive information are agreed during scoping.
Discuss AI security