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OpenFrame Agentic MSP

Automation and Scripting

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Jun 8, 2026Last commit
OpenFrame Agentic MSP is the AI automation layer of the OpenFrame platform, delivered through two embedded agents: Fae, a client-facing AI, and Mingo, a technician-side AI. Together they automate the repetitive work of MSP operations, from first client contact to backend execution, while keeping a human in control of every consequential action. Fae handles the front line. It turns plain-language client requests into structured tickets, runs diagnostics automatically by pulling logs, screenshots, and system information up front, posts proactive status updates, and escalates to Mingo or a human technician when judgment is needed. Mingo handles execution. It generates PowerShell, Bash, and Python scripts on demand, enforces patch and policy compliance, runs bulk operations across hundreds or thousands of devices at once, and records every action with full audit context. Every automation runs inside built-in guardrails: approval gates for risky actions, custom policies that define what runs hands-free, complete audit trails, and one-click rollback. Because Agentic MSP layers on top of the OpenFrame core, it draws on the same unified telemetry, RMM, PSA, and SIEM data already in the platform rather than bolting AI onto disconnected tools. Agentic MSP is delivered as a managed AI layer with usage-based pricing, billed per token. It is designed for MSPs that want to cut ticket volume and manual remediation without giving up oversight or moving operations off a unified platform.
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Key Features

AI Client Agent (Fae)

Fae turns plain-language client requests into structured tickets and runs diagnostics automatically, pulling logs, screenshots, and system info up front.

AI Technician Agent (Mingo)

Mingo generates PowerShell, Bash, and Python scripts on demand and executes fixes across the fleet.

Natural-Language Intake

Clients describe issues in plain English and Fae creates and routes the ticket instantly.

Automated Diagnostics

Logs, screenshots, and system information are collected up front, so technicians skip the back-and-forth.

Bulk Remediation

Push scripts and policy changes across hundreds or thousands of devices in a single action.

Patch and Policy Enforcement

Keeps endpoints updated and compliant without manual policy chasing.

Pros and Cons

Pros

Cuts Ticket Handling Time

Fae automates intake and diagnostics, reducing manual triage and first-response time.

Bulk Execution at Scale

Mingo runs scripts and policy changes across thousands of devices in one action.

Human-in-the-Loop Safety

Approval gates, policies, audit trails, and rollback keep AI actions controlled.

Built on a Unified Platform

Shares telemetry, RMM, PSA, and SIEM data with OpenFrame instead of bolting AI onto disconnected tools.

Multi-Language Scripting

Generates PowerShell, Bash, and Python, covering Windows, Linux, and macOS fleets.

Cons

Cloud-Delivered AI Layer

The agentic layer runs as a managed cloud service and is not part of the self-hostable core.

Usage-Based Pricing

Per-token billing can be harder to forecast than flat per-seat pricing.

Pricing Still in Beta

Token pricing is not yet finalized, so total cost is hard to model today.

Newer AI Product

Fewer public case studies and benchmarks than established MSP automation tools.

Requires Platform Adoption

Most of the value comes when used alongside the broader OpenFrame platform.

Feature Comparison

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