Government
Casework, eligibility, public accountabilityMake citizen-facing AI reviewable by design
Public-sector AI fails commercially and operationally when it cannot be explained, challenged, or halted before it affects a citizen outcome. KLA creates the runtime control path needed for oversight without forcing agencies into a full technology reset.
Operational Bottleneck
The workflow pain
Oversight teams do not need another slide about responsible AI. They need a concrete path for blocking, reviewing, and replaying the decisions that matter.
Casework and eligibility
Require human review before a recommendation changes a citizen outcome, notice, or prioritisation decision.
Transparency and oversight
Retain the exact decision lineage needed for appeals, inspector reviews, and internal accountability.
Govern in place
Add controls to existing public-sector systems without forcing a full rip-and-replace of operational infrastructure.
Governed examples
- Eligibility assistants that recommend but cannot finalise without review
- Casework copilots that draft but cannot send notices without oversight
- Internal knowledge assistants that are governed before they influence public outcomes
What oversight asks for
- Reviewer and agency workflow path for every escalated decision
- Source context, tool calls, and output lineage for the final action
- Retention and replayability for oversight, appeals, and internal investigation