solving the security gap that most people will soon see as harness

I am a head of cloud security for a company that handles $80B worth of payments yearly.

AI Agents in our env were casually taking decisions on what IAC templates needs to be deployed, SRE team called it "deployment at scale and continuous" but this had opened a very unique problem, we could see the AI Agents events on Cloudtrail because of attached AWS IAM, but no visibility into these AI Agents events like what was the prompt that lead to this decision, what URLs did this agent visit, what files did it read or what mcp tools did this agent call ?

One of these agents actually deleted our production S3 bucket with customer data because it thought a drift during a service deployment was too trivial.

and that is exactly why i have been building Burrow for solving runtime security, visibility, and threat detection for AI Agents, Co-Pilots, Gateways and Personal Assistants.

You can essentially define security controls in plain english, for example, "Block Claude code from running git push origin main --force" or "block any agent from reading my aws credentials" Our backend will deep create controlled policies for your agents with full simulated tests and dry runs.

In cases you want to be alerted if your agent is deviating from what is instructed, you can create alerts for it, that say like,

"raise a critical alert when crewai:researcher agent reads aws credentials and tries to exfilterate via curl or equivalent"

Oh and btw, we have an internal service named "lookout" that runs a couple of AI agents on your events that lets you further investigate what exactly went wrong ?  and quarantine the agent on the runtime.