Multinex Shield
Multinex Shield is the zero-trust security layer for AI workflows. It helps teams screen prompts, files, browser sessions, and tool actions before sensitive work reaches unmanaged AI surfaces.
Protect everyday AI usage
Shield gives teams a practical AI security perimeter. It helps users work with AI while policy, redaction, and review controls reduce the chance of sensitive data leaving the organization.
Use Shield when the blocker is trust: prompts, files, browser workflows, and tool actions need visible controls before AI usage spreads across the team.
Choose the right Shield rollout
Individuals can start with local browser protection. Teams should choose a seat tier that matches the number of users, the sensitivity of the data, and the level of audit evidence required.
Policy setup
Start with the data you most need to protect: customer records, credentials, payment details, legal material, healthcare information, or internal files. Then map Shield policy to the AI tools your team already uses.
Vertical compliance shields
Shield supports industry-specific review patterns so teams can explain what AI usage is allowed, what needs review, and what should be blocked before it leaves the workflow.
- Legal workflows: privilege-aware review posture for AI usage
- Healthcare workflows: protected health information handling expectations
- Financial workflows: sensitive payment and account-data handling expectations
- Developer workflows: secret and credential handling expectations
Extension quick start
Use the browser extension path when you want immediate protection on public AI surfaces. Teams can then add shared policy controls and evidence export as adoption grows.
How to evaluate Shield
Use this page to decide whether the product solves the immediate bottleneck: forgotten AI context, sensitive-data risk, or uncoordinated agent work. Then follow the lowest-risk setup path and prove one workflow before expanding.
Multinex Shield decision path
Shield is a fit when the value is clear to the user who has to do the work, not only to the team buying the platform.
- Confirm the user problem this product removes first.
- Run one practical setup path and verify the outcome.
- Add the next Multinex layer only after the first proof is useful.