Sessions
Every agent task is a durable conversation. Open it, watch the plan, inspect run events, review files, approve risky actions, request changes, continue the thread over time. Nothing about the work is hidden in a black box.
Managed AI Ops. We run the platform you build with us.
PRESHai operates the agent runtime, evaluation harness, observability layer, and approval routing across your engagements. The platform is PRESHos. The work is yours. The evidence is auditable.
WHAT MANAGED AI OPS IS
The team that runs your AI in production, with the evidence to prove it works.
Managed AI Ops is the operating partnership that comes after AI Implementation. We built the agents, configured the platform, and trained your team. Now we run the platform alongside them: monitoring evaluation rubrics, watching approval routing, keeping the audit log clean, deploying improvements as the business changes.
PRESHos is the platform that makes this work. Sessions for every agent task. Environments scoped per client. Plugins that connect to your operating systems. Approvals that route by risk class. Audit logs the CFO can read. We operate it. You see everything.
INSIDE THE PLATFORM
What Managed AI Ops actually looks like.
Three views from PRESHos showing how agent work runs in production: managed sessions with governed workflow evidence, human-in-the-loop approvals on the actions that matter, and the governed tool policy that defines what each agent may do.
AGENT OPERATIONS
Every agent task lands in a reviewable session.
Open a session and see what the agent completed: validated packages, attached review assets, and work items routed for approval. Progress and linked files stay with the session so operators can inspect the run and keep the work moving.
- Session history at hand. Switch between health checks, syncs, and reviews without leaving the console.
- Governed workflow evidence. Completed actions and approval progress remain visible after the run.
- Files linked to the work. Preview assets, production proof, and audit attachments travel with the session.
HUMAN APPROVALS
Risky actions stop at a visible human decision.
PRESHos routes the work, artifact, decision context, and reviewer into one approval record. The agent can prepare and recommend. Only the assigned human can authorize the action that moves work forward.
- Full work context. Review the final artifact and linked work item together.
- Named decision owners. Approval authority is explicit, not inferred by the agent.
- Audit evidence retained. The recommendation, decision, artifact, and resulting action stay traceable.
GOVERNED TOOL POLICY
Every agent gets explicit authority—not blanket access.
PRESHos resolves one enforceable policy from the agent's tools, plugins, MCP servers, and subagents. Operators can see exactly what is allowed, what requires approval, and what is disabled before the agent runs.
- Least-privilege by agent. Access is scoped to the work each agent is expected to do.
- Controls operators can read. Allowed, approval-bound, and disabled actions remain visible.
- Evidence on every action. The effective policy and execution trail stay attached to the run.
THE RUNTIME
What runs inside PRESHos.
The four pieces that make agent work durable in production. We operate each one for you, end to end.
Environments
Per-client scoped tool grants, knowledge stores, secrets, and approval policy. Different work, different controls. The agent inherits the environment; the environment inherits the engagement.
Plugins
The actions agents can take. CRM writes, project task readers, knowledge search, approval routing, deployment checks, vertical-specific tools. Built per engagement, reusable across the program.
Approvals
Human-in-the-loop on the actions that matter. Risky writes route to the right reviewer with full context attached. Audit logs travel with the work.
FOR MSPs AND SOLUTION PROVIDERS
A delivery command center, scoped per client.
For IT solution providers and MSPs, Managed AI Ops becomes the operating layer for client delivery. Each client or project has its own Agent Environment with scoped documentation, SOPs, credentials, tools, network policies, and approval rules.
Agents triage tickets, generate remediation plans, audit M365 or Google Workspace settings, draft client-facing updates, prepare onboarding tasks, validate backups, compare configs against standards, create implementation PRs, and run sandboxed scripts safely before human approval. The work travels with its evidence.
- Per-client environments with scoped credentials
- M365 and Google Workspace audit agents
- Backup validation and configuration drift detection
- Sandboxed remediation scripts with approval gates
LIFECYCLE
How agent work actually runs through Managed AI Ops.
From delegation through delivery, every agent task moves through a defined sequence with evidence captured at each step. The team that uses the system sees the same picture you do.
01
DELEGATE
Task assigned with scope and tools.
02
PLAN
Agent proposes the work and approval boundaries.
03
RUN
Sandbox executes with live event stream.
04
REVIEW
User inspects evidence, files, traces.
05
APPROVE
Routing rules apply, audit log captures.
06
DELIVER
Outcome ships to system of record.
USE CASES
Where Managed AI Ops earns its keep.
TICKET TRIAGE
Tier-1 ticket triage with technician hand-off.
- Before
- Tier-1 ticket volume keeps technicians on commodity work and slows down the cases that actually need expertise. Client communication varies by who happens to pick up the ticket.
- With PRESHai
- Agents triage in PSA, draft client responses, and escalate with full context. Technicians focus on the problems that need their judgment.
- Governance
- Approval routing on customer-facing communications. Run history auditable per ticket. Human review on actions outside policy.
CONFIG AUDIT
M365 and Google Workspace audits on a cadence.
- Before
- Configuration audits compete with reactive work and rarely get a regular cadence. Compliance evidence is collected manually when an auditor asks.
- With PRESHai
- Agents run audits on schedule, surface drift, generate compliance evidence packs, and draft remediation plans for human review.
- Governance
- Read-only access by default. Remediation actions gated by approval. Evidence packs stored in audit trail.
BACKUP VALIDATION
Continuous backup validation with test restores.
- Before
- Backups can pass green and still fail when the restore actually matters. Structured test cadences are hard to staff.
- With PRESHai
- Agents test restores in sandbox, validate integrity, log results, and escalate failures with diagnostic context.
- Governance
- Sandboxed execution. Restore tests never touch production. Evidence packs available to client and auditor.
ONBOARDING PREP
New client onboarding tasks prepared end-to-end.
- Before
- Onboarding work is repetitive but needs to be done right every time. Quality varies across technicians and implementation handoffs leave gaps.
- With PRESHai
- Agents prepare account skeletons, document baseline configs, draft kickoff packets, and schedule cadences. A human reviews and ships.
- Governance
- Templates approved by leadership. Per-client review gate before client-facing artifacts ship.
CLIENT UPDATES
Weekly client status updates synthesized from real activity.
- Before
- Status updates either summarize from memory or slip past the cadence. Account managers spend the time on writing instead of on the relationship.
- With PRESHai
- Agents synthesize updates from PSA, project tools, monitoring data, and ticket activity. The account manager reviews and sends.
- Governance
- Data scoped per client. Approval gate before any client-facing send. Audit log records every send.
INFRA-AS-CODE
Implementation PRs reviewed against client standards.
- Before
- Manual configuration changes drift from documented baselines. Reviews catch issues only after a merge has already shipped.
- With PRESHai
- Agents draft PRs aligned to client standards, run validation, surface diffs against baseline, and route for engineering approval.
- Governance
- Sandbox execution. PRs always require human merge. Audit log captures every change.
BEFORE THE RUN PHASE
Managed AI Ops runs the system. AI Implementation builds it.
Most clients engage both as one continuum. AI Implementation gets the agents into production with your team: strategy, deployment, integration, change management, and training. Managed AI Ops keeps them running, governed, and improving as the business changes.
Strategy without operations is a slide deck. Operations without a build phase has nothing to operate. Both happen together.
See Managed AI Ops in operation.
A real demo against a real workflow. Tell us where AI ambition is stalling and we will show you what the operating layer changes.