Governance

Your AI is only as useful as the record behind it.

Calculations run in tested code; inputs are traced to their source. The record stays in the institution’s hands, stored as the work happens rather than reconstructed from a model’s explanation.

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The risk

A fluent answer is not a record.

Most AI systems can produce language. Institutions need provenance: what was checked, what was unresolved, and why a result was allowed into a deliverable.

Reported figure No supporting source attached.
Model input Input and memo disagree.
Approval path Escalation was skipped before delivery.
Committee memo Unresolved work appeared final.
The mechanism

Aperture closes the gap before delivery.

Trace Calculations run in tested code; inputs are traced to their source. Unresolved results are shown, never hidden.
Preserve Sources, tool calls, and agent actions remain attached to the work.
Gate If a required check is open, delivery is blocked, whatever any model reports.
Evaluation

A model earns its role through evaluation.

Each model is tested on the role’s own tasks and runs only if it passes the role’s evaluation. A better model earns the role the same way, without rebuilding the agents.

No silent model swaps. No lost lineage. No hidden source conflicts.

Evaluated Admitted Recorded
What the institution keeps

Your teams make the decisions. The record behind them stays yours.

The record carries forward when you change models, clouds or vendors, within your retention rules and data licenses, and Aperture never withholds it.

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