AI engineering teams are moving agents from single-user demos to multi-user enterprise deployments, and authentication breaks first.
A prototype can run on environment variables or a shared service account. A production agent that acts across tenants, users, and enterprise systems needs delegated authorization, credential isolation, policy enforcement, and audit trails. Without that layer, teams inherit credential drift, rate-limit collisions, broad API keys, inconsistent policy decisions, and confused deputy risk from indirect prompt injection attacks.
The right platform depends on what the agent needs to do: execute governed actions for users, connect quickly to many tools, sync product data, extend an identity layer, or secure infrastructure around the agent.
This article compares the available platforms across authorization enforcement, credential management, deployment model, tool execution, consent and approvals, and auditability.
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