Frequently Asked Questions

SuperIT is an AI agent that resolves real IT incidents and service requests for your end users — autonomously, safely and around the clock. It is not a ticketing tool, a chatbot or an RMM. It sits alongside your existing stack as your “system of intelligence”, cutting across the traditional tool silos so it can actually do the work an engineer would, rather than just triage or summarise it. We are ex-MSP operators, and we built SuperIT to scale the kind of exceptional, personal support that gets harder to deliver as a team grows.

No — and that is not what our customers want. Almost every MSP we speak to is growing and struggling to hire, so they use SuperIT to take on far more than level-one: it resolves the repetitive requests and genuinely complex incidents alike, so you can grow without adding another tech for every new client. That frees your engineers for the human, high-value work software can’t do — building relationships and improving your clients’ businesses, not just running workflows. And the tail of issues that still needs a person? SuperIT hands those over with full context.

It depends on your environment and how much autonomy you switch on, but we set clear targets and measure against them: 25% of in-scope tickets resolved end-to-end within 30 days, 50% within 90 days, and more than 80% over the long term. What surprises most people is that SuperIT is often strongest on the hard, long-tail problems — one design partner had a laptop freezing for four months that even a factory reset could not fix; SuperIT root-caused a deep registry permissions issue and resolved it in about five minutes.

No — SuperIT is the opposite of a ticket-deflection tool. End users already try to solve their own problems before they reach out; they Google it, they ask ChatGPT, and they only contact you when they are stuck and frustrated. SuperIT gives them a genuinely capable way to get unstuck fast, and the moment it cannot help — or the user asks for a person — it escalates straight to your team with everything it has gathered. You can name it, brand it as your own, and keep the human touch front and centre.

ChatGPT and Copilot can tell an engineer what to check; SuperIT does the work. We are a harness over the leading frontier models that gives them what a raw chatbot does not have: a live Digital Twin of the device and environment, your curated knowledge and Skills, and the ability to safely run commands and take action. So instead of copy-pasting commands back and forth, the agent diagnoses and resolves end-to-end.

Most tools in the category are either chat-and-triage layers (a bot asks questions, then a human takes over) or workflow/RPA tools that only run the pre-scripted automations you build first. SuperIT is built to resolve the long tail of issues you cannot pre-script: it works out the right action in the moment using the Digital Twin and your Skills, then runs it safely. We are not trying to replace your PSA or RMM — we are the intelligence layer on top, and we will happily integrate with workflow tools like Rewst and Pia where you already use them.

It does not replace your RMM — it runs side-by-side with it. Our own AI agent (lightweight and available on Windows, Mac and Linux) gathers rich technical detail in an AI-friendly way, which is what feeds the Digital Twin and lets SuperIT safely see and help fix things on the actual machine.

The Digital Twin is a live knowledge graph of your environment — users, devices, hardware, applications, networks and how they all relate — with key metrics snapshotted over time. It is how the agent perceives the environment the way a seasoned engineer would, so it can reason about the real issue instead of guessing. Because it tracks patterns over time, it can answer things like “what changed” or “what was running when this started”.

On top of the frontier models’ general IT knowledge, SuperIT builds a living library of “Skills” from the highest-signal source we have found: your tickets. We have learned that resolved tickets and their notes are often a more accurate picture of how your environment really works than a knowledge base that has gone stale. Every night it “dreams” — distilling new learnings from conversations and tickets back into the knowledge, and flagging anything outdated. It does not need to be 100% perfect to be effective, because the agent can only ever do what you have allowed it to.

You decide, and it ramps up as you get comfortable. Pilots usually start conservative — internal notes only, engineer-driven — then progressively enable more autonomy. Sensitive actions run behind an approval matrix (for example, a password reset on a global-admin account must be approved by a named group), and if there is any risk of going in circles, it escalates to an engineer rather than wasting the user’s time.

Through the channels they already use — directly via your ticketing system, a web chat, a Microsoft Teams or Slack bot, or embedded in your existing customer portal (CloudRadial, Desk Director). We deliberately do not make people learn a new tool or change how they ask for help. The agent adapts its tone too: concise and non-technical for an end user, more technical for an engineer.

Security is the one thing we never compromise on, and it is built in layers, like an onion. There is a hard, system-level filter of dangerous commands that nobody — not an engineer, not the agent — can override; static analysis of every command before it runs; an allowlist and blocklist you control (we ship read-only and non-mutating by default); and, most importantly, the agent inherits the permissions of the person it is talking to, so it can never do something that user could not do themselves. Anything beyond that requires explicit human approval.

Yes. Beyond the allowlist you control, certain system-level commands are hard-blocked and cannot be enabled, even if a human explicitly asks. Credentials and sensitive configuration — like passwords in your documentation tool, or Microsoft 365 global-admin — are kept out of the agent’s reach, and higher-risk actions route through approvals with alerting. Some areas, such as servers and registry edits, are deliberately out of scope today; we expand that envelope carefully and in consultation with you.

SuperIT runs on Google Cloud’s Vertex AI in an isolated tenant, with data encrypted in transit and at rest. We are a model-agnostic harness over the leading frontier models (Anthropic, Google and OpenAI), and we can change which models we use as their performance changes.

We host in Australia and the United States, and because we run on Vertex AI we can pin inference to a specific region where you need it. If you have strict residency requirements — for example regulated, government or law-enforcement clients — tell us and we will configure the right endpoints. For us that is a configuration change, not a major engineering lift.

We are working toward ISO 27001, and also toward SOC 2 compliance — our controls and documentation are in place and we are progressing to formal audit. In the meantime we are happy to share our security and trust documentation and walk your team through the architecture, and we run a bug-bounty program because we would genuinely rather you try to break it.

We are vendor-agnostic and integrate across PSA and ticketing (ConnectWise, Autotask, HaloPSA and more), identity and cloud (Microsoft 365, Entra ID, Google Workspace), documentation (IT Glue, Hudu), RMM, networking and security tooling, and the portals your users already live in. We have built a framework that lets us ship a new integration in about a week — and if a connection does not exist yet, the agent simply gets out of the way and escalates rather than guessing.

Less than you would expect, and we do the heavy lifting. It starts with a read-only API key to your PSA so we can run a ticket analysis — no disruption to production. From there we build your knowledge base and Digital Twin in the background, deploy the agent to a test customer, and expand from there. Most partners are up and running in about three to four weeks, with a dedicated engineer and a shared Slack channel the whole way.

Yes — it is the best way to see the value with zero risk. With a read-only key we analyse a sample of your closed tickets from the last few months and estimate, ticket by ticket, what SuperIT could have resolved end-to-end or shaved off in triage time. You get a tangible report — and a dollar figure — before anything touches production.

Pricing is a fixed monthly fee plus usage-based “AI work credits” — not per-seat and not per-device — because a small MSP using it heavily can get more value than a large one barely touching it, and our real cost scales with the work done. The fixed fee gives you budget certainty; credits are consumed by valuable outcomes like resolving a ticket end-to-end. Our philosophy is simple: you should keep the large majority of the value SuperIT creates.

A short, low-risk evaluation — typically 30 to 90 days — where we agree up front what success looks like, with a headline bar of at least 25% of in-scope level-one tickets resolved autonomously and no security surprises. We do the onboarding, you shape the product to your team, and you can walk away if it is not delivering. Early partners also get heavy founder attention and a real say in the roadmap.

Two ways. Before you commit, the ticket-analysis report shows what SuperIT could have automated across your real history, in hours and dollars. Then we measure against that baseline during the pilot. The ROI is in leverage: your engineers handle more without you hiring the next level-one — which matters, because labour is the largest cost in most MSPs.

We are early, and we are transparent about it. SuperIT is already in production with design-partner MSPs and has been built and tested against millions of historical tickets, but you will find a few rough edges at the margins — we will always be candid about what is still maturing. The one thing we never compromise on is security. The upside of working with us now is real influence over the product, and founders who will be in the trenches with you.