Employee AI Workspace · Current prototype
Ask, attach and analyse in one workspace. Mantle makes the controls visible before an approved model receives the exact payload, so trust can be verified rather than assumed.
Three ways to deploy
Every option uses the same Mantle workspace and governance controls. The difference is who manages the environment, where data is kept and which AI models are connected.
Mantle provides and runs the workspace, approved AI connection and product updates. Your team signs in and starts working without setting up its own model account.
Mantle is deployed in a dedicated cloud environment with the organisation's chosen region, storage and access controls. Mantle can operate it with the client's technology team.
Connect an existing commercial or privately hosted model to Mantle. Employees keep one familiar workspace while the organisation keeps its model contract, account and routing choices.
The same employee experience, data controls, human approvals and evidence records come with every option.
Product demonstration
Before information reaches an external model, Mantle shows exactly what will be kept, masked or removed—and why.
Control language
Product capabilities
Evaluate information in the context of the work rather than treating every field identically.
Govern how organisational data is classified, minimised, approved, exposed, routed, retained and evidenced in AI workflows.
Keep deterministic organisation rules as the final authority over what AI may receive.
Show users and reviewers the precise payload before an external model call is made.
Escalate ambiguous or higher-risk situations instead of silently allowing them.
Support approved routes chosen by task, data classification and organisation policy.
Record governed decisions around AI work without retaining raw removed values.
Align access and actions with organisational authority—not simply model capability.
Architecture in development
Data
AI
Action
Pilot and design partner conversations
Start with one workflow, one team and one real policy boundary. We’ll explore where AI can create useful productivity without sacrificing control.