The distinction between "X% confidence" checks on output vs deterministic authorization on actions/tools is spot on. We've seen the same pattern - probabilistic guardrails at the text level are the weakest enforcement point.
Building in this space too (visibility layer at toran.sh, policy enforcement at keypost.ai). One thing we've found: before you can enforce policy on tool calls, you need to actually see what's happening. The "no clean way to stop, inspect, or intervene once execution starts" problem often starts with lack of visibility into what calls are being made in the first place.
Curious how you handle the observability → enforcement gap. Do you assume teams already have visibility into their agent's API calls, or does AxonFlow provide that inspection layer as well?
Building in this space too (visibility layer at toran.sh, policy enforcement at keypost.ai). One thing we've found: before you can enforce policy on tool calls, you need to actually see what's happening. The "no clean way to stop, inspect, or intervene once execution starts" problem often starts with lack of visibility into what calls are being made in the first place.
Curious how you handle the observability → enforcement gap. Do you assume teams already have visibility into their agent's API calls, or does AxonFlow provide that inspection layer as well?