Your queue grows and you can't add people. Managed AI Ops puts a team of AI agents to work inside your Breeze instance — triaging alerts, patching fleets, resolving tickets — while you hold the approvals. We read the AI's work, verify it, and tune it with you. And because quotes and invoices live in the same platform, the team can carry work through to billing: see the whole loop.
Not for everyone. Curated intake, supervised from day one.
What the team actually does
Every action is classified, logged, and reversible. The operator proposes; your risk engine decides.
Examples are representative. The operator's exact responses depend on your fleet state, policies, and risk classifications.
Supervision
Every helpdesk chat the AI handles is reviewed. We verify resolutions held, catch drift early, and fold what we learn back into the agents. You get the capacity without becoming the AI expert.
Patch 3 domain controllers — client BlueRidge
Proposed window: tonight 02:00–04:00 · Rollback plan attached
Why it needs you: domain controllers are Tier 3 by your policy.
Approved actions run, log, and report back. Everything else waits.
Representative interactions. The team's real work depends on your fleet, your policies, and your approval gates.
Click through the live UI
Tool catalog
Every RMM capability is exposed to the operator as a standardized tool. Each tool has a risk tier. The same reboot is Tier 2 inside a maintenance window and Tier 3 outside one. Context drives policy automatically.
List devices, get details, query fleet state
Retrieve, update status, link to tickets
Reboot, shutdown, lock, isolate, install, uninstall
Status, schedule, deploy with maintenance windows
PowerShell, Bash, or Python with result retrieval
Compliance, security, inventory, executive reports
The math
Not a replacement for your people — capacity for them. Your seniors stop doing password resets.
Thirty minutes. You bring the workload; we tell you honestly whether the AI team fits.
Two ways to run the AI
You are the AI team's manager.
Same Breeze. Same tools. Same risk engine. The difference is who does the work.
The AI team can request actions. Your Breeze instance decides whether to allow them. Risk classification is enforced at the RMM level, not the AI level — the same guardrails apply whether a human tech, the built-in operator, or the managed team is doing the work.
Every action is auditable. Every tool call is logged. Every approval decision is recorded.
Rung two
Breeze AI for Office puts a governed AI assistant in front of your clients' end users, starting with Excel — with your name and logo on the pane. Sensitive data is scanned and redacted before the model ever sees it, writes show a before/after preview and wait for approval, and IT sets the policy: who gets access, read-only mode, budgets, audit trail.
Explore AI for Your Clients/Users →
Every business will run on AI. Your clients will get it from whoever manages their technology — that should be you, not a stranger.
Where to next
The in-app AI assistant with risk-tiered actions and full audit trail.
AI that can take direct action on endpoints under guardrails.
Hierarchical configuration policies that govern what the AI can do.
The reports the AI team generates automatically: compliance, security, executive.
FAQ
A team of AI agents, run by the people who built Breeze, that works your fleet and your queue inside your own Breeze instance: alert triage, patch operations, ticket resolution, fleet hygiene, and reporting. Every action is governed by the 4-tier risk engine you control — reads run free, low-risk fixes auto-execute with an audit log, impactful actions wait for your approval, and destructive actions are blocked.
We do, with you. We read the AI's ticket conversations, verify its resolutions actually held, and tune the agents as your fleet and clients change. You never have to become an AI expert — that is the product. You keep the approvals; we keep the quality.
The risk engine bounds it, the audit trail shows it, supervision catches it, and a human — ours or yours — finishes the ticket. Impactful actions never execute without your approval, and every tool call is logged and reversible where reversal is possible.
Only within the limits your risk engine defines. Tier 1 reads run freely. Tier 2 low-risk fixes auto-execute and are audit-logged. Tier 3 impactful actions — reboots outside maintenance windows, domain-controller patches, agent uninstalls — require human approval. Tier 4 is blocked outright. The risk engine is enforced at the RMM level, not the AI level.
Billing is tailored to your fleet and workload, on self-hosted or cloud Breeze, with support included. As an anchor: it costs a fraction of the technician hire it replaces. It starts with a call, not a checkout.
Yes. Every Breeze deployment includes the built-in AI operator free — bring your own Anthropic API key and it runs locally in your instance under the same risk engine. Managed AI Ops is for teams that want the working team and the supervision, not just the capability.
In a deliberately small, curated form. We take on engagements we can supervise properly, design-partner style, and we are honest that this is early. If the fit is right, your AI team can be working your queue within days.
A supervised AI team, inside your RMM, behind your approvals. It starts with a call.