Platform | Technology
For AI agents
Enforce runtime, identity-aware authorization for agents in your workforce to control every action they take across sensitive systems, tools and data.
Agents are already privileged actors inside your environment.
AI agents have moved quickly into enterprise workflows, but access management programs have not kept pace. Most agents still inherit broad permissions from users, service accounts or other non-human identities, giving them more reach than any given task requires.
When agents interact with sensitive systems or enterprise data, standing access introduces unacceptable risk to the business. Without runtime access control, there is no clear boundary for what an agent should be allowed to do, and no kill switch should something go wrong.
Solution
Authorize every action at runtime.
P0 replaces static permissions and implicit trust with runtime, policy-driven access control.
Every agent's action is evaluated before execution based on identity, context and risk. Instead of provisioning broad roles or long-lived credentials, P0 authorizes the exact access required for the task - with precise, auditable control that keeps work moving - and revokes access when the work is done.
Controlled autonomy
"AI agents don’t fail because they’re malicious, they fail because they’re given too much trust."
Control any agent touching sensitive data and systems.
P0 centralizes how agent actions are evaluated, enforced and audited across your production environment.
With the P0 AuthZ Control Plane for Agents, every access decision is made before execution, ensuring agents can only act within approved scope, for limited time and always with full accountability.
Discover all agents and MCP servers that exist
Auto-discover agents, tools and users with sensitive access as environments scale.
Control access with end-to-end policy enforcement
Enforce policy at runtime directly in target systems with blended identity context.
Prove what happened every step of the way
Audit agent activity, access decisions, policy changes and permission drift across the full chain.
“Claude Code is reshaping our access risk model. Engineers could use agents to automate scripts on remote servers or access sensitive data on production databases.
One unintended command, rm–rf or mkfs, executed with an engineer's authority, can have catastrophic consequences. Every agent action needs to be evaluated against policy at runtime, not after the fact.”
Venkat Venkatraju
Cloud Security Engineer at Splunk
“Every agent action needs to be evaluated against policy at runtime, not after the fact.”