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Managed intelligence

AI that someone is responsible for on a Tuesday.

The demo always works. The question is what happens in month seven, when the model behind it has been retired, an integration has quietly broken and nobody noticed. That gap is what a managed service is for.

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In short: an AI managed service covers four things: monitoring so failures are caught before customers find them, maintenance as models are retired and integrations break, ongoing improvement as the business changes around the system, and an accountable support path with a response time. Anything missing those is a licence rather than a managed service. AI4SMB provides it for Australian small businesses, built on an MSP with 32 years of running business systems to an SLA.

What it includes

Four things. Most proposals cover one.

Monitoring

Something watches whether it is actually working, and tells us before it tells your customers. AI fails softly: it does not usually throw an error, it gives a confident wrong answer that nobody catches for a month. That is what monitoring is for.

Maintenance

Models get retired, APIs change under you, integrations break when the other party ships an update. None of that announces itself. Somebody has to be responsible for the thing continuing to work in six months, and that is the difference between a build and a service.

Improvement

Reviewing what it is getting wrong and correcting it. An AI system left alone does not quietly improve, it quietly drifts as your business changes around it. Prompts, rules and escalation paths get revisited on a schedule rather than after a complaint.

Accountability

A support path with a response time and a person attached. When it misbehaves, the question "whose job is it to fix this" needs to have had an answer before it happened.

The tiers

They stack, and you start where the audit says.

01

Tier 1 - Receptionist managed + monitoring

02

Tier 2 - + workflow automations maintained

03

Tier 3 - + AI-managed content/SEO engine (what this site demonstrates)

Monthly rates are not published yet. Retainer pricing is set per business against scope and volume, and it comes out of the audit. We put a price up the moment a real quote exists, which is how the audit came to be listed publicly at from $800 ex GST, and we would rather leave this blank than invent a number.

Why an MSP

The AI part is new. The running-it-properly part is not.

Everything that makes a managed service worth paying for was invented long before AI: monitoring, backups, patching, change control, an SLA, and someone whose job it is to answer the phone when it breaks. Those are not AI skills, they are operational ones, and they are what PearceIT has been doing for Australian small businesses for 32 years. The reason we frame AI as infrastructure rather than as a product is that we have watched what happens to business technology that nobody owns. It does not fail on the day it is installed. It fails eighteen months later, on a Friday, and by then the person who set it up has moved on.

Proof, such as it is

This website is tier three, running in public.

The top tier is an AI-managed content and SEO engine, and rather than describe it we run it on ourselves and publish the numbers. An AI builds and maintains this site, measures its own visibility in AI answers and search, and reports the results at /experiment, including the failures. As of the day-50 read that includes a checkpoint missed by twenty days and a flagship search target we are nowhere near, published alongside the wins. You can judge whether the product works by looking at the only customer it currently has.

Managed AI, straight answers

What does an AI managed service actually include?
Four things, and the first one is the one that gets skipped. Monitoring: something watches whether the AI is working and tells us before it tells your customers. Maintenance: models get deprecated, APIs change, integrations break, and someone has to keep it running. Improvement: reviewing what it is getting wrong and correcting it, because an AI left alone does not get better. And accountability: a support path with a response time, so when it misbehaves there is a person whose job it is to fix it. If a proposal does not cover all four, it is a licence, not a managed service.
Who will run and maintain AI systems for my business?
We will, and the relevant background is that this is the same discipline as managed IT rather than a new one. AI4SMB is built on a managed services provider with 32 years behind it, so monitoring, patching, backups, change control and an SLA are things we already do for a living. The AI part is new; the running-it-properly part is not. That is the whole argument for buying this from an MSP rather than from an AI startup that has never carried a pager.
Why does AI need managing at all? Is it not just software?
It degrades in ways ordinary software does not. Traditional software does the same thing forever until you change it. An AI system sits on top of models that get retired and replaced, prompts that drift out of date as your business changes, and integrations to other people's services that move under you. It also fails softly: rather than throwing an error, it gives a confident wrong answer that nobody notices for a month. That last one is the real argument for monitoring, because the failure mode is silent and your customers find it before you do.
What are the tiers?
Three, and they stack. Tier one is a managed AI receptionist with monitoring. Tier two adds your workflow automations, maintained rather than just built. Tier three adds the AI-managed content and SEO engine, which is the thing this website is a live demonstration of. Most businesses start at tier one or come in through an audit and land wherever the roadmap says they should.
What does it cost?
The monthly rates are not published yet, and rather than invent a number we would rather say so. The pattern on this site is that a price goes up the moment a real quote exists, which is how the audit came to be listed at from $800 ex GST. Retainer pricing is set per business against scope and volume, and it comes out of the audit. What we can tell you now is that it is priced as a service with a response time attached, not as a per-seat licence.
Is this the same as "managed intelligence"?
Yes. Managed intelligence is the term emerging in the MSP industry for exactly this: the operational discipline of managed IT applied to AI systems. We use it deliberately and we have written a plain-English definition of it. The short version is that it treats AI as infrastructure that has to keep working rather than as a product you buy once.
Do I have to start with a retainer?
No, and we would usually advise against it. Start with the audit so there is evidence about what is worth automating in the first place. A retainer on top of automations nobody needed is an expensive way to maintain a mistake. Build first, prove it pays, then decide whether it needs managing.

Automation nobody maintains is a liability with a subscription.

Book an audit call. We will tell you what is worth automating, and separately whether it is worth paying anyone to keep running.

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