Zenity watches the agent. The breach plays out in Salesforce, Workday, and your third-party apps.

Both platforms secure AI agents. The difference is the layer each platform prioritizes and the data each one reads.
Copilot Studio and Zenity help govern the agent build layer: prompts, behavior, and tool calls. But once Copilot agents are live, they act inside SaaS apps like Salesforce, ServiceNow, Workday, and M365 through OAuth tokens and service accounts.
That’s where Zenity can struggle. Without native SaaS connectors and SaaS logs, it’s hard to show what the agent actually did inside the receiving app, what permissions or app configurations enabled it, and which verified identity or service account was behind the action. Obsidian reads that SaaS and identity context natively, so you can understand the agent’s real downstream impact across apps.
Both enforce at runtime. The difference is what each policy reads when it fires. Agent-side runtime can control what an agent does at the tool-call level. Obsidian extends runtime decisioning with SaaS state, identity, and permissions, so policies can be more specific over time: for example, don't touch a file in OneDrive labeled sensitive, when the agent was built by a specific user, calling on behalf of a specific identity. That granularity comes from reading the receiving app's state and identity context, not just the agent's tool calls.
Inventory is only the starting point. Obsidian shows who built the agent, who ran it, and what the service account inside the SaaS app is permissioned to do. That gives defenders the context to understand which agents create real business risk and align configuration to that risk.
You can, but there's meaningful overlap at the agent-platform layer. In shared AI platforms like Copilot Studio, both products may rely on similar agent-platform telemetry. The cleaner answer is to pick the platform that also reads the SaaS and identity context the other doesn't.
Posture detection tells you an agent looks risky. By the time a posture finding lands, the agent has often already executed. Runtime enforcement fires at the tool call, before the action completes. Both platforms have moved to runtime for this reason. The remaining question is what each runtime can read: agent inputs and outputs alone, or also the SaaS state and identity context that decide whether the action is actually risky.
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These come from real customer environments, including customers who've evaluated Zenity and Obsidian.
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