Reduce the platform work required before the first business outcome
Managed AI agent infrastructure
Build transformation, not platforms.
Use a Microsoft Azure-based cloud foundation for provisioning, persistence, model routing, usage, health, and lifecycle.
The operating problem
From pilots to measurable change.
The hidden cost of an agent program is the control plane around it: provisioning, identity, isolation, state, usage, recovery, and day-two operation.
Expected outcomes
Start with verifiable value.
Create agents from consistent Organization standards
Operate a growing fleet through shared health and lifecycle controls
Expand from verified outcomes instead of infrastructure experiments
Platform evidence
Designed around operating realities
Repeatable provisioning
Luna creation follows a visible sequence with recoverable states.
Shared observability
Admins see fleet status, ownership, health, and basic usage in one experience.
Controlled expansion
Agent-count and budget boundaries help an Organization scale deliberately.
Start the transformation
Create the first operating capability.
Define the systems, permissions, review points, controlled user group, and evidence required before expansion.