Access control
Map users, roles, systems, approval owners, and task boundaries before agents can run.
Control layer
Make access, actions, and evidence visible.
WonderWave helps companies plan local AI controls around access, approved sources, bounded agents, review trails, and retained evidence. The goal is practical governance your team can operate.
What gets controlled
Security starts with limits people can inspect.
Controls need to be specific enough for IT, operations, and reviewers to understand what AI may do and what must stay blocked.
Audit trails
Record requests, approvals, denials, model routes, runtime state, source use, and reviewer decisions.
Approved sources
Keep source libraries explicit so agents work from known material and uncertain inputs can be reviewed.
Prompt injection risk
No setup eliminates prompt injection. WonderWave reduces exposure with source limits, tool permissions, review gates, and evidence.
Model poisoning risk
Model and data routes need review. Approved sources, retained evidence, and route records help teams see what influenced work.
Sandbox limits
Sandboxes help, but they are not the full control plane. Teams still need authority rules, action gates, runtime visibility, and review.
How WonderWave helps
Turn controls into an operating routine.
WonderWave does not claim to eliminate every AI security risk. It helps reduce exposure by bounding access, making actions reviewable, keeping records visible, and documenting the handoff for your team.
Before workAuthority and source rules
Define users, tools, systems, data categories, sources, and approval paths.
During workBounded execution
Use scoped tools, time limits, model routes, runtime checks, and review gates.
After workEvidence review
Inspect what ran, what stayed blocked, which source was used, and who approved the result.