Client delivery
Define the workflow, approved information, review process, and responsibility for the delivered result.
Managed AI Operations / Industry context
Managed AI Operations for Agencies
Repeatable AI delivery needs cost visibility, client boundaries, and a dependable operating handover.
Start with the work your team needs to improve.
Repeatable AI delivery needs cost visibility, client boundaries, and a dependable operating handover.
Automation oversight
Make scheduled work, failed runs, and incomplete handoffs visible to the delivery team.
Provider coordination
Review model changes, usage attribution, and client-specific access boundaries.
The work needs an owner after deployment.
We agree the business outcome, the systems involved, and the evidence needed to judge the result. An implementation is useful when the team can see whether it ran, whether the output met expectations, and who handles the next step.
Client permissions, licensing, and brand approval remain explicit parts of delivery. White-label specialist work is scoped through the MSP and partner program.
- A business sponsor and accepted outcome
- Approved access and data boundaries
- A baseline for cost, quality, and reliability
- A clear escalation and change process
- A handover and next improvement backlog
Choose the service layer that fits the responsibility.
01 / Understand & improve
Private betaElevated AI GatewayRouting · Budgets · Access · EvidenceOptional control layer. Start with your existing tools.Blueprint
Two weeks to map the environment, baseline cost, and implement one improvement.
$7,500 fixed02 / Operate & optimizeVirtual AI Ops
A named operator, a regular review cadence, and an owned improvement backlog.
Starting at $5,000/month03 / Add control when justifiedManaged Private AI
A tailored deployment when your requirements make private AI the right choice.
Optional · scoped implementationYour business assets and operating responsibilities.
You own your data, business-specific AI assets, and the work Elevated AI creates for you. Foundation models remain subject to their own licenses. Portability depends on those licenses and the agreed architecture.
The Blueprint’s fixed scope includes one implemented improvement. Further work is agreed based on the model, data, integration, security, hosting, and operating needs involved. The initial discussion should make those boundaries clear before access or implementation begins.
Quick answers
How does an engagement start?
The AI Operations Blueprint is a fixed $7,500 engagement that reviews your current AI environment, establishes a cost baseline, designs an operating architecture, and implements one agreed improvement in two weeks. You leave with working progress, clear ownership, and a practical next-step plan. The fee is fully credited toward a qualifying implementation or managed-services agreement.
Can you work with our existing systems and IT team?
Yes. We begin with your current environment, approved access, and responsibility boundaries. Your team or MSP retains its core IT and business approval responsibilities.
Do we need a private model or Gateway?
No. We evaluate provider APIs and your existing controls first. Private AI is optional; Elevated AI Gateway is private beta and is not required to begin.
What happens after implementation?
The agreed handover defines ownership, evaluation, and support. Virtual AI Ops can supply a named operator and continuing reviews, starting at $5,000/month.
Make the next step concrete
Put an operator behind your AI.
Start with a two-week Blueprint. Leave with an operating plan and one improvement already in place.