Tools that authenticate human users, manage single sign-on (SSO), and enforce multi-factor authentication (MFA) across enterprise applications. They were built to give employees, contractors, and customers secure, federated access to the applications they need.
User IAM tools solve a foundational problem: who is this person, are they who they claim to be, and which applications should they be able to access? They work well for human authentication: login flows, MFA policies, session management, and federated SSO across SaaS applications. The gap appears when the identity in question is not a person at all — a microservice making API calls, an AI agent executing tasks across multiple systems, or a CI/CD pipeline deploying infrastructure. None of these have a login flow, a session, or a browser.
A common anti-pattern emerges: teams create service accounts as “users” inside Okta or Entra ID to plug the gap, ending up with machine identities living in a system designed for humans — overprovisioned, ungoverned, and invisible to access review workflows. Aembit is the purpose-built home for those machine identities: think of it as the “Okta for workloads.” It provides machine identities the same level of policy enforcement, visibility, and lifecycle control that traditional IdPs provide for employees.
Aembit also integrates with your IdP in two concrete ways: for administrative access to the Aembit platform itself, and for blended identity in agentic AI scenarios, where the user is redirected to their IdP to authenticate, and Aembit combines that user context with the AI agent’s workload identity to make a single, high-fidelity access decision.
Aembit does not replace your IdP. It handles the workload identity layer that your IdP was never designed to cover, and it works with your IdP for admin sign-in and blended identity.
Aembit connects to your IdP in two distinct ways, both of which make the tools more useful together.
The first is administrative access. Aembit supports SAML 2.0 and OIDC identity providers for administrator sign-in, meaning your security and platform teams log into the Aembit platform using the same IdP they use for everything else. Okta, Microsoft Entra ID, Google Identity, and any SAML 2.0 or OIDC-compliant provider work natively.
The second is blended identity for agentic AI. When an AI agent acts on behalf of a human, Aembit can redirect the user to their IdP to authenticate, capture the resulting user context (name, email, group memberships, OIDC claims), and combine it with the AI agent’s workload identity into a single access decision. The result is a blended identity: Aembit knows both who authorized the task and what workload is executing it. This enables access policies that express rules like “engineers can use Claude Desktop to access Jira, but only the security team can use it to access the vulnerability scanner,” or “revoke this specific user’s AI agent access without affecting others or rotating shared credentials.” Neither the IdP alone nor the agent runtime alone can enforce these kinds of policies.
User IAM and Aembit solve different problems at different layers of your infrastructure. An IdP like Okta or Microsoft Entra ID governs human identity: it knows that alice@company.com is authenticated, belongs to the engineering group, and should have access to certain SaaS applications. That model depends on a person — there is a login event, an MFA challenge, a session token, and a logout. None of that machinery applies to a microservice, a data pipeline, or an AI agent running autonomously.
The anti-pattern that fills the gap is also the most common security debt in enterprise identity programs: service accounts created as users in the IdP. A team needs a pipeline to authenticate to an API, so they create a service account in Okta or Entra ID, assign it an API key, and move on. That account accumulates permissions over time, has no human owner, never goes through an access review, and persists long after the system that needed it is gone. Aembit eliminates this pattern by providing a purpose-built runtime for machine identities — not as users in the IdP, but as attested workloads with short-lived credentials and policy-driven access controls.
Your IdP continues to govern who your employees are and which applications they can reach. Aembit governs which services, agents, and pipelines can reach which APIs, databases, and internal tools — at runtime, without static credentials. And in agentic AI scenarios, the two work together: the IdP authenticates the human, and Aembit combines that authentication with the agent’s workload identity to enforce access policy that accounts for both.
PAM handles human privileged sessions: an admin checking into a production server, a developer accessing a cloud console, a vendor connecting to a sensitive system. Ambit handles the other side: applications, services, Al agents, and CI/CD pipelines that need to authenticate to those same sensitive systems without human intervention. PAM is optimized for the relatively small number of human administrators in an environment – session-based, interactive, with approval workflows and session recording. A microservice or Al agent operating at scale makes thousands of authentication requests per hour, has no interactive session, and cannot wait for a human approval workflow.
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