Safe agent operations on top of trusted signal infrastructure.
The AI Agent Gateway matters because it shares gateway health, simulator, and receipt context with the same control plane human operators already use.
- MCP resources
- Signed receipts
- Approval-aware actions
Context that matches the dashboard and the operator workflow.
Installation state
Can the agent tell whether the gateway is receiving signals and which path is actually active?
Signal health
Can it explain delivery quality, recent failures, and security events using the same inputs the dashboard uses?
Allowed actions
Can it tell the difference between safe reads and approval-gated changes?
The agent layer should be safer than the average dashboard workflow.
Use the gateway as an agent-readable control plane
The immediate value is diagnostic: validating installations, explaining signal health, listing failures, and recommending the next operator action without inventing hidden state.
Make infrastructure operable by humans and AI systems
That is the differentiated category story: first-party signal infrastructure that works traditionally for humans and natively for agent-operated workflows when the trust model is strong enough.
Get one gateway live before the next planning cycle.
Start with a single first-party path, validate delivery with the simulator and health views, then scale the same infrastructure across paid channels and agent-ready operations.
Best for operators who want to test immediately inside the dashboard.
Start freeBest for teams migrating off another setup or planning a multi-gateway rollout.
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