We used to split our view of risk: AppSec tools looked at the code, cloud tools looked at the infrastructure, and nobody owned the full picture for the agents that sit on top of both. In reality, the marketer was writing the Python, the analyst was shipping the agents, and those agents call the APIs, touch the containers, and invoke serverless functions across clouds. Orca ties the application, cloud, and agent context together in one unified model. When there’s an issue, we can see the agent, the vulnerable code it relies on, the service it runs on, and the data it touches—all in a single view.

We are constantly creating with AI agents, and compliance used to feel completely disconnected from that reality. Teams ship agents to production, analysts wire agents into workflows, PMs push agent-backed features, and then audit season arrives with the spreadsheet. Orca continuously maps our cloud workload and agent posture to the frameworks we care about, tied directly to the resources and agents that power what we build.

We build across AWS, Azure, and GCP. Different teams own each cloud and ship features independently, and our AI agents follow those same paths, calling services across multiple providers at once. Before Orca, that meant three different stories about where the agents lived and what they could reach. Orca connects to every account and subscription and gives us a single, contextual view of the risk tied to the AI agents and the services our business depends on. Our CISO can see the agents, their identities, and their blast radius across clouds in one place instead of chasing separate dashboards.