Knowledge capture, ticket triage, ramping junior techs, and the real economics of automation for small MSPs. Written by an MSP operator, not a marketing team.
Most MSPs who try AI support tooling hit the same wall at month two: the bot is no smarter than day one. That's not an AI problem — it's a feedback-loop problem. Here's what compounding actually looks like when the loop is closed.
Read the post →AI vendors claim 90%+ accuracy — but rarely show the math. Here’s how to measure confidence, grounding, and false-positive rate yourself before you trust any classifier.
Read the post →The ticket that sits for five days and then gets mass-closed to clean the queue doesn’t just clutter your board. It quietly leaks the resolution data your KB, your billing, and your AI all depend on. Here’s why tickets rot, and how to stop it.
Read the post →Most “AI helpdesk” vendors say “trust us.” We publish the framework instead: the L1–L5 trust ladder, dry-run mode, and a per-type circuit breaker that catches a bad auto-send before it ever reaches a client.
Read the post →Solo MSPs hit a ceiling not because of tools but because senior knowledge doesn’t scale. Here’s the auto-documentation stack that changes that.
Read the post →Before you buy an AI helpdesk for your MSP, ask these 7 questions. Most “AI helpdesk” content is bundled-PSA marketing. Here’s the vendor-agnostic truth.
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