Runtime Enforcement

Guardrails that understand the whole session.

Intent-aware enforcement on agentic action, decided on the device and tuned to how each team works.

Why rules alone fall short

Agents rarely break a rule in one obvious step. They get there one reasonable-looking action at a time, often by trying another route when the first one fails. A rule that only sees the last command can’t tell a routine task from one that’s drifting.

Bay reads the whole session, understands what the agent is trying to do, and applies your policies at the moment it acts.

How it works

01

Intent-aware, decided locally

Bay reads each agent’s whole session to understand its intent, then decides on every action: allow, ask, deny or steer. Every decision is made locally, in milliseconds, with no cloud round-trip.

The Bay console listing the top AI tools in use, with actions, sessions and risky actions
02

Guardrails tuned to each team

Bay applies out-of-the-box policies from day one. Lighthouse, Bay’s agentic policy-building system, then learns from 30 days of agentic history and writes and tunes guardrails for each team as it changes.

Two Bay finding summaries, one critical and one resolved, with severity and affected endpoints
03

Test in simulation first

Run any policy in simulation to see what each rule would allow, ask, deny or steer, before a single user is affected.

The Bay console listing the top AI tools in use, with actions, sessions and risky actions
04

Steer agents back on course

Long-running agents work when no one is watching. When agent intent or actions drift from policy, Bay tells it how to finish the job according to your guardrails, and the work carries on instead of stopping.

Two Bay finding summaries, one critical and one resolved, with severity and affected endpoints

Live in 5 minutes. Tailored in an hour.

Deploys through your MDM or EDR. 

No proxy: every decision is made on the device.