Use cases · where intent verification matters
The work that has to be provably correct.
Verification matters most where the cost of an unintended action is real and irreversible — money moved, code deployed, credentials issued, a robot arm in motion. The same gate that decides for a coding agent decides for a payment bot and a surgical robot, because they all resolve to one shared vocabulary: 173 canonical intents across 29 domains, 14 digital and 15 physical.
01 · How to read these
One runtime, not four products.
These are not four separate integrations — they are four boundaries the same Authority Token surface guards. The interpretation, the risk model, the conformance scoring, and the cryptographically signed, replayable audit chain are identical across all of them. What changes is the connector and the canonical domain the action anchors to. Pick the boundary that hurts most if an agent gets it wrong; the rest of the runtime is the same underneath.
02 · Anchor domains
DevOps — coding agents at the deployment boundary
Every production deploy, merge, rollback, and schema migration an autonomous SDLC agent attempts is intent-verified, token-gated, and audit-sealed before the runner moves.
DevOps →Financial — bots at the payment boundary
Refunds, transfers, subscriptions, payouts, approvals. Authority Tokens are single-use and TTL-bounded; replay is refused at the gate. Receipts by construction.
Financial →Security — SecOps automation, on a leash
Credential rotation, access provisioning, incident response, remediation. The same model that decides for engineering agents decides for the most-privileged agents you run.
Security →Compliance — regulated workflows, end-to-end
Sequence conformance scored against your declared process. Continuous control, not a quarterly sampling exercise. Evidence that holds without us in the loop.
Compliance →03 · Beyond the digital four
The same grammar reaches physical motion.
The four anchor domains are the most common entry points, but they are four of 29. The taxonomy carries 15 physical domains for embodied AI — manipulation, locomotion, autonomous vehicles, surgical robotics, energy, and embodied-AI safety. An authority decision reads the same whether it gates a git push or a robot’s grasp, which is what lets one governance layer span both halves.