Generating documentation. We don't have a product manager. Instead, our system watches what the engineering team ships and automatically generates reference docs, tutorials, and feature specs from the source code. We talk about the time it hallucinated setup instructions that didn't exist, how we fixed the trust hierarchy between generated docs and manual notes, and why auto-documentation is the single biggest force multiplier for a small team.
What's included in OpenFrame? Does it integrate with my existing tools?
OpenFrame isn't built to plug into your stack. It replaces it.
Instead of duct-taping a dozen tools together (RMM, MDM, SIEM, patching, remote access, each its own login and bill), we bundle it into one unified platform: RMM, MDM, monitoring, automation, remote access, patch management, security monitoring, and ticketing, plus built-in AI copilots.
So "does it integrate with X?" usually means: you won't need X anymore.
How is OpenFrame different from other vendors?
Most platforms give you one piece and expect you to bolt the rest on. OpenFrame unifies the whole stack in one place, with AI copilots built in. Fewer logins, fewer bills, less duct tape.
Is OpenFrame for MSPs or MSSPs?
Both. It's built for MSPs and MSSPs alike.
Where is my data hosted?
In the cloud, on US soil. Your data stays stateside.
MSP AI Agents
Can AI Agents Really Close Tickets Without a Technician?
Yes. In production MSP shops today, 10% to 25% of tickets close before a human opens them. Thread alone has processed 173 million tickets across 750-plus MSP partners at 96% triage accuracy, handing back 490,000-plus technician hours. Agents own the low-risk, high-volume work (password resets, MFA enrollment, known installs, onboarding and offboarding) and flag anything that touches production data or needs judgment for a human to take.
How Much Can AI Agents Save an MSP?
On a five-person desk, reported deployments show $78,000 to $130,000 in annual direct labor savings, roughly 30% fewer escalations, and 15% to 20% better SLA compliance. Broader MSP adoption data adds ticket handling time cut by 45% and five to 12 points of margin, all from reclaimed capacity rather than headcount cuts.
AI MSP
How Are MSPs Using AI?
MSPs use AI to triage and route tickets, cut alert noise, schedule patches, assist L1 security work, and draft client reports. Kaseya's 2025 benchmark found 30% already use it to eliminate tedious tasks, with ticket triage the most common starting point.
What AI Tools Do MSPs Use?
Most MSPs start with AI features inside their existing PSA, RMM, and ticketing systems rather than standalone products. Common categories include AI ticket triage, alert correlation, scripting assistants, and AI-native all-in-one platforms like OpenFrame that run intelligence across the whole stack.
Where Should an MSP Start With AI?
Start with a readiness assessment, not a tool purchase. Confirm your ticket history is clean and your RMM, PSA, and monitoring systems connect. Then pick one high-volume, low-risk workflow, usually ticket triage, and pilot it on internal tickets before any client sees it.
Which Tasks Should an MSP Automate First?
Automate high-volume, low-risk tasks first. Ticket triage and alert noise reduction top the list because they run constantly and a human still resolves the underlying issue. Save security approvals, billing changes, and client-facing actions for later, always with a human in the loop.
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