mBase
Let the business see who uses AI, what it costs, and which data is allowed.
mBase provides a direction for governing model and token usage, access, budgets, routing, cost, and audit within agreed deployment scope.
What can improve
Improvement to pursue
- 01
See model and usage boundaries
Keep available models, use cases, and limitations in one governance context.
- 02
Put access and budget into policy
Manage access and cost ownership by role, work, and risk.
- 03
Retain cost and audit basis
Keep usage, approval, and exception records available for review.
Organize model choices
Map model choices by work need, capability, and limitation.
Start with the use case before deciding which model enters the flow.
Set usage policy
Show how role, access, purpose, and cost ownership connect.
Follow policy to check that usage stays within control.
Keep governance records
Show how usage, approval, and exceptions form reviewable records.
Retain a governance basis for later checking and adjustment.Customer use cases
Start with the work the team must complete, not a feature checklist.
- Enterprises that already use multiple models or accounts and need visibility into access and usage
- Organizations able to define policy with IT, finance, or the team responsible for AI usage
Token pool
Manage department, plan, and model usage centrally.
Model and access governance
Choose allowed models by work, data, and risk.
How work improves
Keep effective existing systems and connect the work in practical stages.
- 01
Inventory
Map models, teams, accounts, and work.
- 02
Set policy
Allocate budget, access, routing, and limits.
- 03
Observe
Track usage, cost, anomalies, 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