mDock
Let AI handle more system work within clear boundaries.
mDock manages AI tools and system connections, staff approvals, error handling, and activity records so teams can review or stop automated actions.
What can improve
Improvement to pursue
- 01
Connect systems within control
Place systems, skills, and data exchange inside explainable connection boundaries.
- 02
Reduce manual process watching
Let routine actions proceed by risk, routing only high-impact decisions involving money, personal data, or external commitments to an authorized person.
- 03
Retain execution and exception evidence
Keep traceable work records for every connection, execution, and failure.
Map system connections
Show how systems, skills, data, and triggers connect.
Define what should be exchanged before opening a connection.
Route high-impact exceptions
Separate AI suggestions, tool execution, and necessary human decisions by risk.
Let routine work continue while people handle high-impact exceptions.
Track execution exceptions
Show how success, failure, and pending work become records.
Hand exceptions to an owner instead of letting them disappear silently.Customer use cases
Start with the work the team must complete, not a feature checklist.
- Enterprise IT, operations, and governance teams
- Organizations connecting AI to systems and actions
Controlled connectors
Let AI read or act within explicit permissions.
High-impact exception
Route authorized decisions before sensitive actions.
How work improves
Keep effective existing systems and connect the work in practical stages.
- 01
Register capability
Define the skill, connector, and allowed scope.
- 02
Check risk
Set access, approval, and exception behavior.
- 03
Record each action
Preserve inputs, outcomes, and audit history.
How it works with other systems
Show only the product relationships needed to complete this work, without replacing every system at once.
Start with your work