Tenant isolation
Tenant context should stay bounded at the gateway layer. The public site should make that separation legible before a buyer asks for architecture details.
MSPlex connects AI to production MSP systems, which means trust cannot be implied. This page explains the public posture: tenant isolation, managed auth handling, and how to think about evaluation before implementation details move into a deeper review.
Tenant context should stay bounded at the gateway layer. The public site should make that separation legible before a buyer asks for architecture details.
MSPlex is designed to keep auth handling in a managed exchange layer instead of scattering credentials across every AI client and workflow definition.
Security review is part of operational fit, not an afterthought added after a workflow already exists.
Buyers should be able to see where credentials live, what the gateway passes forward, and which surfaces never receive secrets at all. This is the clearest public explanation of the managed boundary before a deeper review begins.
Vendor credentials stay encrypted at rest until the gateway needs them.
The request carries only a credential reference, not the secret itself.
A broker retrieves the secret just in time and scopes it to the tenant making the call.
The connector uses the secret in process memory only while the vendor request is in flight.
The execution window closes and the secret does not persist in the worker after the call completes.
Confirm which systems and actions matter in your environment, especially where credentials and tenant scope are most sensitive.
Map how tenancy, auth, and returned data should behave before the first rollout conversation moves into implementation details.
Use the connector and experience surfaces to understand the operational model in public-safe terms before asking for deeper detail.
Bring the remaining questions into the contact flow so the evaluation can move from public posture to environment-specific review.
Public pages should establish the trust model and answer the first questions. Deeper environment-specific detail belongs in the evaluation process, not in generic marketing copy.
The right next step is not vague reassurance. It is a direct discussion about the systems you run, the workflows you want AI to touch, and the trust boundaries that matter in your environment.