Stream Security named Gartner Cool Vendor

From Shadow AI to Detection and Response: Closing the Visibility Gap at Machine Speed

AI workloads are dynamic, abstracted, and deeply embedded into modern applications, making them hard to track with traditional security tools. This creates a growing “shadow AI” problem where models, agents, and tools operate without oversight. Our AI workload discovery solves this by continuously analyzing cloud-native logs and runtime signals to identify all AI components in your environment—including hosted services, models, tools, and MCP servers. Each component is correlated to the workload executing it, the identity behind it, and its behavior over time. By baselining this activity, security teams can quickly spot anomalies such as new models, unauthorized integrations, or unusual usage patterns. More importantly, this visibility feeds directly into detection and response, enabling full attack storylines that include the AI layer.

From Shadow AI to Detection and Response: Closing the Visibility Gap at Machine Speed

You Can't Prompt Your Way Out of Bad Data: Why Context, Not Models, Wins in the Cloud

Making SecOps
Cool Again.

Find out more about how we are transforming Cloud Detection and Response:

Birth of the Cool: Bringing Cloud Context to SecOps Teams

We wouldn’t believe it either.