Standing watch over every agent.
Know what it's doing – and why.
CerberusAI helps enterprises take control of their AI agents. Watch every agentic action with our leading behavioral analysis technology and shut down rogue agents before they do damage.
The questions keeping security teams up.
Your company put agents to work faster than security could keep up. Those agents now hold credentials, reach your data, and act on their own.
How many agents do we actually have?
Most teams can't give a headcount, let alone say who launched each one.
What are they touching?
Agents reach data, tools, and systems through credentials nobody reviews after day one.
Would we know if one was turned against us?
A poisoned tool, an injected prompt, or a compromised account can turn a working agent into an insider threat.
How fast could we stop it?
CerberusAI responds in near real time, while the agent is still running, before a bad step becomes an incident.
Your existing tools judge each step independently, without context.
Agents take one task and turn it into a chain of tools, data, and actions. Every link can look fine in isolation. The threat is in the sequence.
Pattern of life, applied to agents.
An intelligence analyst never judges a target on one event. You build a baseline of normal, then watch for the break. CerberusAI does the same for every agent, and Intent-Based Analysis™ holds each step up against the agent's tasking.
One watch across every agent.
CerberusAI sits in the path of your agents' model and tool traffic, so your security team gets one picture of what every agent touches.
Up and running
without slowing anyone down.
Your builders keep shipping. Your team reviews the alerts and sets the containment threshold. Personal data is hashed at the source, so raw values never leave your environment.
Sits in the path of your agents' model and tool traffic.
Watches the tool calls your agents make to MCP servers.
Built from the intelligence world.
CerberusAI was founded by a naval intelligence officer who spent 8 years tracking actors and reading their intent, and an ML engineer from Airbnb, Apple, and Tesla Autopilot.
The method is the same one used to follow people of interest: establish a pattern of life, attribute every action to the actor behind it, and raise the flag when intent turns hostile. We point it at the agents your company now depends on.
Read Tradecraft, our field notes →