Decision Timeline
Follow one interaction
Trace received, normalized, evaluated, and reviewed records with explicit observed and derived labels.
Cross-protocol observability
Monitor Agent Transactions Through Evidence
Agentic commerce monitoring connects normalized events, policy outcomes, authority explanations, review state, and attribution confidence without assuming that every AI referral executed a checkout.
Current product boundaryEvent intake, Decision Timeline, Authority Map, and Review Inbox operate in OBSERVE.
THE OPERATING MODEL
Transaction counts are useful only when their semantics are clear.
An AI referral, agent-executed checkout, payment event, refund, return, and physical inventory movement are different facts. Monitoring keeps them separate and records which source supports each classification.
The workspace follows an interaction from accepted Agent Event through normalization, evaluation, Decision Receipt, authority explanation, and human review. Partial or late evidence remains visible on the Timeline.
WHAT THE RECORD MUST SHOW
Monitoring joins operational state without flattening it.
Authority Map
Explain effective authority
See identity, delegation, mandate, policy, scope, expiry, revocation, and evidence state in context.
Review Inbox
Resolve bounded questions
Give authorized operators the exact policy and evidence context for a time-limited human disposition.
EVIDENCE FLOW
From incoming event to an inspectable workspace
- 01Accept a versioned Agent Event
- 02Deduplicate equivalent delivery
- 03Normalize provider evidence
- 04Evaluate the applicable policy
- 05Issue a Decision Receipt
- 06Project Timeline, Authority Map, and Review state
CLEAR PRODUCT BOUNDARY
Monitoring does not manufacture attribution or outcomes.
A URL, app identifier, referrer, marketing event, or SDK claim does not prove agent execution. AgentGateFee preserves source-specific evidence and confidence instead of turning weak signals into transaction facts.
COMMON QUESTIONS
Understand the evidence before changing the workflow.
Does every duplicate delivery count as another event?
Equivalent idempotent deliveries reconcile to the same accepted event identity and do not create another usage record.
Can monitoring distinguish AI referral from agent checkout?
The model treats demand source, last touch, checkout actor, checkout mechanism, confidence, and evidence as separate dimensions. Availability depends on the integration evidence supplied.
Does monitoring change an order or checkout?
No. The current workflow is read-only OBSERVE governance and performs no customer action.
START WITH EVIDENCE