I built an AI co-pilot into MSPercury for solo and small MSPs. It handles invoicing, quoting, time-logging, and customer-portal replies — all from chat. Here's what it does, what it deliberately doesn't, and why I built it the way I did.
Per-user, per-device, or all-you-can-eat? A practical 2026 pricing framework for solo and sub-five-tech MSPs — with baseline numbers, what to include in the base, and what to bill extra for.
Autotask, ConnectWise, Halo PSA were built for 20-tech MSPs with full-time admins. For a solo or sub-five-tech shop in 2026, the contract lock-in and per-tech minimums no longer pencil out — and a new tier of tools is finally honest about that.
Embed a self-service IT security check on your MSP website with a single iframe. Visitors get an honest IT maturity score in about three minutes — and you get a fully qualified lead with a PDF report, no sales call needed first.
Most SaaS tools that ship AI features lock you into their LLM and stack a markup on every token. MSPercury's AI runs on your own API key — Anthropic, OpenAI, or any OpenAI-compatible endpoint. Here's why that matters for an MSP.
Every MSP turns down customers they can't serve. We built a partner network that lets them hand those leads to peers who can — with zero money flow between users, double-opt-in consent baked into the workflow, and a karma system that rewards reciprocity. Here's the architecture and why it stays cleanly outside ZAG, MiCA and GwG scope.
Five minutes to embed on your marketing site: a self-service IT security check that gives prospects a maturity score in under 3 minutes — and drops a fully qualified lead with PDF report straight into your pipeline. GDPR-compliant, branded with your logo and color, no sales call required first.
Most quoting tools were built for inside-sales reps, not for the engineer who just walked out of a customer's server room. Here's how that gap shaped the product.
The audit you can do standing in front of a server cabinet without a laptop. Thirty questions, four categories, photo-able findings — what we ask, in what order, and why.