Aembit Extends Access Controls to Personal AI Agents

Aembit, the identity control plane for AI agents, today announced support for securing personal agents’ access to enterprise environments, available immediately to existing customers at no additional cost.

As personal agents, such as Meta Muse and OpenAI Dots, move into workplace use, they can gain access to email, cloud applications, code repositories, internal tools, and other enterprise services through employee credentials and delegated permissions. That raises the risk of sensitive data exposure, unauthorized changes, and activity that is difficult to distinguish from the employee’s own actions. Those credentials may also be stored in the personal agent platform, outside the security team’s direct control.

Aembit addresses this problem through a blended identity that combines the agent’s distinct identity with the identity of the employee it represents. Organizations can evaluate both at the time of access, as well as issue short-lived credentials for approved requests, record agent activity centrally, and revoke the agent without disabling the employee’s account.

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“Personal AI agents are going to find their way into the enterprise for the same reason personal devices did before them: People use whatever helps them get work done,” said David Goldschlag, CEO and co-founder of Aembit. “The good news is that this is exactly the kind of access problem Aembit was built to solve. Give the agent its own identity, control what it can reach, and shut it off without taking the employee offline.”

With Aembit, enterprises can:

• Give each agent a distinct identity. Personal agents can be recognized and controlled separately while retaining the context of the employee they are acting for.
• Apply access policy at runtime. Aembit evaluates the agent, the user behind it, the requested resource, and applicable conditions before access is granted.
• Replace standing credentials with short-lived access. Approved requests receive scoped credentials that expire, reducing reliance on reusable secrets held by the agent.
• Extend controls across enterprise services. The same identity and policy model can govern access to SaaS applications, developer platforms, and internally built services.
• Centralize audit records. Security teams can trace which agent requested access, who it represented, what resource it reached, and which policy authorized the request.
• Revoke an agent independently. Security teams can disable an individual agent’s access without resetting the employee’s credentials or interrupting the employee’s work.

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Aembit also gives enterprises flexibility in where policy is enforced. Its architecture can work through the Aembit MCP Identity Gateway or with other gateways and enforcement points already deployed in the environment. Identity, authorization policy, and audit remain centralized in Aembit, while each access request can be evaluated dynamically and granted only the access needed for that interaction.

Aembit has formally highlighted support for Meta Muse and also secures access for agents and AI platforms including Microsoft Copilot Studio, Claude, ChatGPT, Gemini, and custom LLM-based workflows.