Approval workflows
Decision classes map to named approvers, escalation paths, and recorded outcomes.
CAPABILITIES / GOVERNANCE AND OPERATIONS
AI governance
The controls that let a risk team sign off: who approved what, on what evidence, and how to reverse it.
What this covers
Audit trails and decision records
Each material run stores its inputs, rule results, model version, and final human action.
Data classification and routing
Policy tags determine which stores and model endpoints may receive a given field.
Access control
Roles and workload identities limit who can view evidence or invoke sensitive actions.
Policy and usage rules
Machine-enforced checks turn written limits into controls that run before each restricted operation.
How it shows up in the work
ENTERPRISESMove governed AI into production.A review queue is a place where trained people apply rules to a stream of items. Agents can carry most of that load, if every decision arrives with the evidence behind it.ENTERPRISESOne platform for a growing agent workforce.The first agent is a project. The tenth is a platform problem. Shared retrieval, model routing, monitoring, and tuning are what make the second agent take weeks instead of months.NATIONSBuild the trusted national data and AI grid.Institutions hold data that would be worth more together, and they're right to be careful about sharing it. A grid makes sharing governed rather than informal.
WHERE IT FITS
Governance requirements are set in discovery, tested in the proof, and maintained during operate.
