Measure activity
Review run history, token usage, request counts, and runtime-impact signals where available.
Agent operations
How do I keep AI agent hosting costs low when agents are idle most of the time?
Keep idle AI agent costs under control by measuring runtime activity, separating active work from dormant tenants, and making lifecycle, schedule, release, and access decisions explicit. Bewize Hub provides the operating layer for tenant lifecycle and usage evidence, so teams can review what is running before changing runtime policy.
A bounded cost-control process
Cost control starts with evidence and lifecycle ownership, not an unsupported promise of a fixed savings percentage.
Separate tenants
Identify which tenant runtimes, schedules, and agents are active, dormant, or blocked.
Control lifecycle
Use explicit release, restart, access, and scheduling procedures for managed runtimes.
Review the trade-off
Balance idle cost, wake-up behavior, response needs, and operational recovery before changing policy.
Operational evidence to connect
Idle AI agent cost FAQ
Does Bewize promise a specific cost reduction?
No. Bewize offers measurable controls and evidence, not a savings percentage or an outcome guarantee.
What should be checked before stopping an idle runtime?
Check tenant ownership, schedules, pending work, access expectations, recovery steps, and the evidence needed to confirm the change.
Which product provides the control layer?
Bewize Hub provides tenant lifecycle, schedules, policies, runtime operations, and usage evidence for managed AI worker runtimes.