Audience 01
AI governance teams
Uses the product where the cost of an unscoped action is higher than the cost of setup.
Knowledge & context · Concept
Where the work actually changes.
DecisionTracing is aimed at AI governance teams, compliance officers, platform engineers, enterprise operators.
01
Who it is for
Three audiences, one boundary model.
Audience 02
compliance officers
Needs the same permission model for people and agents.
Audience 03
platform engineers
Uses the product where the cost of an unscoped action is higher than the cost of setup.
02
Use cases
Each row maps a capability to the operational change it is meant to produce.
| Capability | Operational change | Status |
|---|---|---|
| Decision trace capture | Removes an ad hoc step from the workflow. | Specified |
| Causal and evidentiary lineage | Makes an existing action reviewable. | Specified |
| Tool and action correlation | Turns a manual control into an explicit contract. | Specified |
| Trace validation and replay | Makes an existing action reviewable. | Specified |
| Observability APIs, dashboards and MCP resources | Removes an ad hoc step from the workflow. | Specified |
03
Migration
How a team would move from the status quo without a big-bang cutover.
Step 01
Map the current path
Name the tools, owners and handoffs that the product replaces. Nothing is removed yet.
Step 02
Run one capability
Pick a single scoped capability and run it alongside the old path, with evidence compared side by side.
Step 03
Retire the old path
Remove the previous tool only when the new record is complete enough to audit.