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Home/ AI & Copilot/ Build with AI

Buying AI is easy. Building with it has to be learned.

Your own team building and using AI in your business, on a framework that keeps you out of trouble, with the licensing right, the running cost understood, and somebody alongside them while they learn. We are not trying to become the department you cannot fire. The point of this programme is that in a year your people are building things we never touched, and the only reason we are still in the room is that you find the catch-ups useful.

6Workstreams 24Ideas to start your backlog Your teamOwns what gets built RegularCatch-ups and consulting
The shape of it

We set it up, your team builds, we stay alongside.

Capability, not dependency

Most AI engagements sell you an outcome and keep the knowledge. That works right up until the model changes, the person who commissioned it leaves, or somebody asks a question nobody internally can answer. This one is built the other way round. The deliverable is your people, and the things they build are the evidence.

We do this

Put the foundations in

The framework, the licensing and the guardrails. The unglamorous half, done once and properly, because every mistake worth avoiding in AI is made in the first month by someone with good intentions and an expensed subscription.
Your team does this

Build the actual things

Hands on their own keyboards, in your own tenant, on your own data, starting with a job that already annoys somebody. We are next to them rather than in front of them, and the first build is deliberately small enough to fail cheaply.
Then this, ongoing

Keep showing up

A regular catch-up with the people building, consulting when a decision is bigger than a catch-up, and a quarterly look at what it is costing against what it returned. Including the sessions where we tell you to switch something off.
Workstream 01

A secure framework

Before anybody buys anything
The goal

Rules for AI that a person can actually follow and an auditor can actually read.

A framework is not a document nobody reads. It is the small number of decisions that stop the predictable accidents: confidential material pasted into a personal account, an agent given the permissions of whoever happened to build it, a tool in daily use that nobody ever approved. Written down once, these take an afternoon. Discovered after the fact, they take a lawyer.

  • What may go into a model, what may never, and who decides the grey ones.
  • Business accounts instead of personal logins, so the terms that govern your data are ones you signed.
  • Where the data goes, how long the vendor keeps it, and whether it trains anything.
  • Nothing acts on its own: an agent proposes, a person approves, and the approval is recorded.
  • How a new tool gets approved before somebody expenses it and it becomes a habit.
What you own at the end. A written AI policy, an approved tool register, and a decision record that survives the person who wrote it.
The rule

Nothing goes out on its own

An agent drafts, suggests, flags and queues. Sending a customer an email, posting to the ledger, changing an access right or deleting anything stays with a person. The agent makes the work cheap. It does not make the decision.
The record

Who approved what, and when

Every approval is written down, because the first serious question after anything goes wrong is who authorised it. An agent without an audit trail is one you will have to switch off at exactly the moment you most need to explain it.
The boundary

It sees what its owner sees

An agent inherits permissions. Point one at a file store that has been quietly over-shared for six years and you have not created a new problem, you have made an old one instant and searchable. That is why readiness comes before building.
Workstream 02

The right licensing

Seats for the people who use them
The goal

Stop paying for seats nobody opens, and stop good people working on personal accounts.

The most expensive AI licence is the one bought for everybody because deciding was harder. The second most expensive is the one your best people avoid, so they quietly keep using a personal account with none of the protections you are paying for. Getting this right is mostly a matter of being specific about who does what.

  • Who genuinely needs Copilot, who needs Claude, who needs both, and who needs neither this year.
  • The difference a business tier makes to the data terms, which is the real reason to move off personal plans.
  • Seat licences against credit packs against usage billing, and which of your jobs suits which.
  • Annual against monthly, and what you give up for the discount.
  • A quarterly look at what is assigned against what is actually being used.
What you own at the end. A licence position you can defend line by line, and a renewal date nobody is surprised by.

Here is the field as it stands. Vendor pricing moves without notice, and several of these are billed in US dollars, so we link to each vendor's own pricing page rather than repeat a figure here that would drift. We go through the current numbers with you when we look at who actually needs which seat.

Microsoft Copilot Studio

Hosted
Where it wins

Agents that live where your people already are, inside Teams and Microsoft 365, working on your SharePoint and Graph data with the identity and permissions you already run.

What bites

You are billed per credit, so a popular agent gets expensive quietly rather than loudly. What it can reach is bounded by what the connectors expose, and that boundary is where most projects meet their surprise.

Vendor pricing ›

Microsoft 365 Copilot

Hosted
Where it wins

Helping individual people inside the apps they already have open. It is the per-seat assistant layer across Word, Excel, Outlook and Teams.

What bites

It is an assistant, not an agent platform. It waits to be asked. If you want something that runs on its own and hands work back finished, this is the wrong line item.

Vendor pricing ›

Claude, Team and Enterprise

Hosted
Where it wins

Work that is thinking rather than formatting: long documents read properly, analysis that holds up, and processes built once and reused. It is not tied to one software suite, which is why it handles the jobs that do not fit inside an app.

What bites

It is not natively wired into your tenancy the way a Microsoft product is, so connecting it to your systems is real integration work rather than a checkbox. Billed in USD, so your actual cost moves with the exchange rate.

Vendor pricing ›

Claude API, build your own

Either
Where it wins

An agent you own outright, that runs on your schedule against your systems, with no seat count and no dependence on what a product happens to expose.

What bites

Usage priced, so the bill follows the work rather than the headcount. That is honest but it needs a budget and a ceiling set deliberately at build time.

Vendor pricing ›

ChatGPT Business and Enterprise

Hosted
Where it wins

Broad general capability with the widest staff familiarity, which lowers the training cost of getting a team started.

What bites

Enterprise is quote only and carries a large seat minimum, so the entry point is a procurement exercise rather than a subscription.

Vendor pricing ›

n8n

Either
Where it wins

The plumbing. Moving work between systems on a trigger, with the steps visible on a canvas that a non-developer can actually follow and audit.

What bites

It orchestrates, it does not think. It is the frame you hang a model on, and the cloud tiers are priced by execution volume, which climbs faster than people expect.

Vendor pricing ›

A model you host yourself

Self-hosted
Where it wins

The genuine constraint cases: data that is not permitted to leave your control, a regulator who wants a straight answer about residency, or volume large enough that per-token pricing stops making sense.

What bites

The hardware is the small number. Published analyses put the maintenance at 10 to 20 engineering hours a month, and below roughly 2 million tokens a day an API is usually cheaper than the box, before anyone is paid to look after it.

Vendor pricing ›

We are a Microsoft Solutions Partner and a Claude partner, and we will still tell you when the honest answer is fewer seats. Check the vendor's own page before you commit to a number, and see licensing for how we handle the rest of your subscriptions.

Workstream 03

Optimising token usage

The layer people get surprised by
The goal

The bill follows the work, and your team can see it move before the invoice arrives.

Usage billing is honest but it is unfamiliar, and a team that has never been taught to think about it will build something that works beautifully and costs four times what it needed to. Almost all of that is avoidable, and none of it requires switching vendor. This is the part of the programme that pays for itself most visibly, because the before and after are both on an invoice.

  • Matching the model to the job, because most production work does not need the most expensive one.
  • Sending less: retrieving the three pages that matter rather than the whole library.
  • Caching the part of a prompt that never changes, and batching the work that is not urgent. Both are billed at a lower rate than sending it fresh and immediately.
  • Measuring cost per run rather than cost per month, so an expensive agent is obvious rather than absorbed.
  • Setting a ceiling at build time instead of discovering one at invoicing.
What you own at the end. A cost per run for everything you have built, and the habit of checking it.

If you are paying by usage, this is the meter.

Priced per token, in and out
ModelWhat it is for
Claude Opus 5 The hard reasoning. Worth it when being right matters more than the unit cost.
Claude Sonnet 5 The everyday workhorse. Most production agents should start here.
Claude Haiku 4.5 High volume, low judgement. Classifying, routing, extracting.

A token is roughly three quarters of a word, counted both going in and coming out. The practical read: an agent that reads a hundred long documents a day costs money you will notice, and one that answers forty short questions a day usually does not. The number that matters is not the rate, it is how much you send it, and that is a design decision made at build time rather than a surprise found at invoicing. Current rates are on each vendor's own pricing page.

Workstream 04

Exploring local AI infrastructure

Usually not, and we will show you why
The goal

An evidence-based answer to whether any of this should run on your own hardware.

This question comes up in every engagement, usually second, and it deserves a real answer rather than a reflex in either direction. Sometimes running a model on your own infrastructure is genuinely right. More often the thing driving the question is a control requirement that a business tier already satisfies, and the honest service is to find that out before anyone buys a GPU. We explore it with your team rather than deciding it for them, because the ones who have seen the working do not have to revisit it every six months.

  • What genuinely runs well on a machine you own today, and what still does not.
  • The maintenance bill, which is the number that decides it and the one nobody budgets.
  • The volume at which per-token pricing stops making sense, which is a much higher bar than it sounds.
  • Residency, retention and the straight answer a regulator, insurer or tender wants.
  • The middle options that solve most of it without anyone owning a GPU.
What you own at the end. A decision with the working shown, including the decision not to.

Host it yourself when

  • Your data genuinely cannot leave your control, and you can point at the clause that says so rather than the feeling that says so.
  • A regulator, an insurer or a tender wants a straight answer about where processing happens.
  • Your volume is high enough that per-token pricing has stopped making sense, which is a much higher bar than it sounds.
  • You already employ someone who will still be there in a year and wants to own it.

Do not host it yourself because

  • It feels safer. Feeling is not a control, and a badly run server you own is worse than a well run service you rent.
  • It looks cheaper. Published analysis puts maintenance at 10 to 20 engineering hours a month, which is the real bill.
  • Someone read that it is cheaper at scale. Below roughly 2 million tokens a day, an API is usually cheaper than the hardware before anyone is paid to look after it.
  • You want control. You can get residency, retention and administrative control on a business plan without owning a GPU.

If the answer does turn out to be your own infrastructure, we run sovereign hosting in New Zealand, so exploring it does not mean handing the question to somebody else.

Workstream 05

Agents and autonomous bots

The part everyone asks for first
The goal

Your team can stand one up, and knows the times not to.

An agent is not a chatbot with ambition. It is a piece of software that does a job you would otherwise pay a person to do, hands the work back finished, and waits to be told whether it got it right. Teaching a team to build one is mostly teaching them to choose the job well and to leave a person in the loop on purpose, which are judgement skills rather than technical ones.

  • Telling an assistant, an automation and an agent apart, because they cost and fail differently.
  • Picking a job worth automating, which is rarely the impressive one.
  • Building the smallest version that could possibly work, where you can watch it.
  • Human approval designed in from the start rather than bolted on after the first scare.
  • What to do when the model behind it is replaced, which happens more often than the vendors advertise.
What you own at the end. Working agents, and more importantly the people who can build the next one without us.

Three different things get called an agent.

Only one of them is
Not an agent

An assistant

Waits to be asked, answers, forgets. Copilot in your Outlook is an assistant. It is genuinely useful and it is priced per seat, because the value scales with how many people are sitting there asking.

Not an agent

An automation

Fires on a trigger and does exactly the same thing every time. Enormously valuable, far cheaper, and the right answer more often than anyone selling agents will tell you. If the rules never change, you want an automation.

This one is

An agent

Given an outcome rather than a script, it works out the steps, uses the systems it has been given, and comes back with the work done and its reasoning shown. You want one when the job needs judgement in the middle, and the judgement is the expensive part.

The honest filter. If you can write the rules down completely, build an automation and spend the difference elsewhere. An agent earns its cost when the input varies, the right answer depends on context, and a person is currently making that call fifty times a week. Teaching your team to apply that filter themselves is worth more than any single agent we could hand you.

Five steps, in the order they really happen.

Step two is the one people skip
Step 01

Pick a job that is already annoying someone

Not the most impressive job, the most repetitive one with a clear right answer. If nobody can describe what a good outcome looks like, an agent cannot either, and that is a finding worth having before you spend anything.

You, in an afternoon
Step 02

Find out what it is allowed to see

An agent inherits the permissions of whoever runs it, which means an over-shared SharePoint becomes an over-sharing agent on day one. The permissions problems that trip up Copilot trip up everything else pointed at the same files.

Readiness assessment
Step 03

Build the smallest version that could possibly work

One job, one data source, one person using it. The point is to find out where the real difficulty is, which is almost never where it looked from the outside.

Build session or plan month
Step 04

Put a human in the loop, on purpose

The agent proposes, a person approves, and the system records who approved what. This is the difference between an agent you can defend in an audit and one you quietly turn off after an incident.

Designed in, not bolted on
Step 05

Decide who runs it on the Monday after

Something built and then orphaned is worse than nothing, because people start relying on it. Name the owner before you build, and be honest if the answer is that nobody has the time.

Your team, or a plan
Workstream 06

Experimenting with new ideas

The one that never finishes
The goal

A live backlog, a cheap way to try things, and permission to kill the ones that do not work.

The businesses getting real value are not the ones with the best strategy document. They are the ones running four small experiments a quarter and cheerfully abandoning three of them. That only works if trying something is cheap, if there is a queue of things worth trying, and if stopping is a respectable outcome rather than an admission.

  • Starting from a backlog rather than a blank page. There are twenty-four on this page to begin with.
  • Running an idea as a two-week experiment with a stated success measure, not an open-ended project.
  • The honest filter: if the rules never change, build the automation and spend the difference elsewhere.
  • Writing down what failed and why, so nobody spends the same fortnight again in March.
  • Bringing what is new to you rather than what is new on the internet.
What you own at the end. A backlog your team keeps themselves, and a record of what has already been ruled out.

Twenty-four to start the backlog.

Filter by where they sit

These are not hypotheticals. Each one exists because the manual version of it is already happening somewhere, badly, in a spreadsheet. They are here as a starting queue for your team rather than a menu of things to order from us, and size is relative rather than a quoted duration.

Medium Finance

The invoice coder

Reads every supplier invoice as it arrives, proposes the account code and cost centre, and puts it in front of a person to approve.

Reaches Xero or MYOBthe accounts inboxSharePoint
Guardrail. It proposes the coding. It never posts to the ledger on its own.
Small Finance

The debtor chaser

Drafts the follow-up on every overdue invoice, in your tone, ranked by what is worth chasing first rather than by what is oldest.

Reaches Xeroemail
Guardrail. Drafts sit in a queue. Nothing reaches a customer until someone sends it.
Small Finance

The reconciliation explainer

Takes the transactions nobody can place and searches two years of history for the ones that looked like them, with the reasoning shown.

Reaches Xerothe bank feed
Guardrail. Explains and suggests. The match itself is still a human click.
Large Finance

The quote-versus-actual checker

Compares what each job was quoted at against what it actually cost to deliver, and tells you which kinds of work quietly lose money.

Reaches the job systemtimesheetsXero
Guardrail. Only as good as the join between systems. Getting the keys right is most of this build.
Medium Operations

The job sheet reader

Turns a photographed, scanned or handwritten job sheet into a structured record, and asks a human about anything it could not read.

Reaches the job systema phone cameraSharePoint
Guardrail. Low confidence must route to a person, not resolve to a best guess.
Medium Operations

The supplier price watcher

Reads supplier price lists as they land, flags exactly what changed, and works out what the change does to your margin before you find out at invoicing.

Reaches the purchasing inboxyour price book
Guardrail. Never let it update a price book directly. Changing sell prices is a decision.
Small Operations

The exception triager

Reads carrier and supplier notifications, and separates the ones a customer genuinely needs to hear about from the noise.

Reaches emailthe order system
Guardrail. Draft the customer message. Do not send it automatically.
Large Operations

The procedure writer

Drafts a written procedure from a recording of someone actually doing the task, then re-checks it each quarter and flags the steps that no longer match reality.

Reaches SharePointscreen recordingsthe documentation system
Guardrail. A procedure nobody approved is not a procedure. Publication stays a human step.
Small Sales

The enquiry qualifier

Reads every inbound enquiry, works out who the company is, and drafts both the reply and the suggested next step before anyone has opened it.

Reaches the website formsemailthe CRM
Guardrail. Enrichment from public sources only, and the draft is a draft.
Medium Sales

The proposal first-drafter

Assembles a first draft from your own previous proposals and the notes from the call, so the blank page stops being the reason quotes go out late.

Reaches the CRMpast proposalsmeeting notes
Guardrail. Pricing must come from the price book, never from a previous proposal it happened to read.
Medium Sales

The CRM housekeeper

Finds the duplicates, the records owned by someone who left, and the opportunities that have not moved in a year, and proposes the fix for each.

Reaches the CRM
Guardrail. Merges and deletes are proposals. Bulk edits from an agent are how a CRM gets ruined in one afternoon.
Large Sales

The tender mapper

Reads the tender, maps every requirement to the evidence you already hold, and tells you plainly which ones you cannot currently answer.

Reaches the tender documentyour policy setpast submissions
Guardrail. The value is in the honest gap list. An agent that fills gaps with plausible text is a liability.
Medium People

The onboarding co-ordinator

Turns a start date into the whole checklist, raises the requests across every system, and chases the ones nobody has done by Friday.

Reaches the HR systemMicrosoft 365the ticket system
Guardrail. It can raise access requests. Granting the access stays with the approver.
Small People

The policy answerer

Answers staff questions from your actual policies, quotes the clause it used, and says so plainly when the policy does not cover the question.

Reaches SharePointTeams
Guardrail. Must cite, and must be able to say it does not know. A confident wrong answer on leave or conduct is worse than no answer.
Small People

The timesheet checker

Flags the timesheets that do not look like the person’s normal pattern, before payroll rather than after it.

Reaches the time systempayroll
Guardrail. Flags to a manager. This one never messages the employee.
Small People

The interview structurer

Turns everyone’s scattered interview notes into the same scorecard, so candidates are actually compared on the same things.

Reaches the ATS or a shared drive
Guardrail. It structures what the panel said. It does not score or rank candidates.
Medium IT & security

The alert triager

Takes a security alert, gathers the context from every other system that saw the same device or account, and writes the short summary of what it actually is.

Reaches the monitoring platformthe endpoint toolsthe ticket system
Guardrail. Isolating a device or disabling an account is never the agent’s call.
Medium IT & security

The access reviewer

Lists who can currently reach what, and flags the access that does not match the job the person actually does.

Reaches Microsoft 365the file serverthe line-of-business systems
Guardrail. Read-only. Removing access is a change with a rollback plan behind it.
Medium IT & security

The licence reconciler

Compares what you are billed for against what is actually assigned, and what is assigned against what anyone has used this quarter.

Reaches Microsoft 365the billing export
Guardrail. Reducing a licence count can breach a contract minimum. It reports. You decide.
Large IT & security

The documentation gap finder

Compares what you are being billed for against what is actually documented, and surfaces the things running in your business that nobody has written down.

Reaches the documentation systemthe billing datathe monitoring platform
Guardrail. Findings belong in a dated report, never written silently into a live document.
Medium Legal & risk

The contract register builder

Reads the contracts you already signed and pulls the dates, notice periods, liability caps and auto-renewals into one register you can actually search.

Reaches the contract folderSharePoint
Guardrail. Every extracted term links back to the clause it came from, so it can be checked.
Small Legal & risk

The renewal early warning

Tells you a notice period is closing while you still have time to do something about it, rather than the week it renews.

Reaches the contract registercalendars
Guardrail. Warns early and warns twice. Silence is the failure mode that matters here.
Large Legal & risk

The privacy request mapper

Works out where one person’s data actually lives across your systems, so a privacy request is a task rather than a fortnight.

Reaches Microsoft 365the CRMthe file server
Guardrail. Under the Privacy Act you have 20 working days. Build this before you need it, not during.
Large Legal & risk

The incident timeline builder

Assembles a defensible chronology from logs, tickets and email when something has gone wrong and the question is what happened when.

Reaches the monitoring platformthe ticket systememail
Guardrail. Evidence handling matters. This one is built to preserve, never to tidy.
Yours is not on the list?
Good. The list is the obvious ones, and the obvious ones are rarely the most valuable thing in a particular business. Describe the job and we will tell you honestly whether it is an agent, an automation, or something you should not build at all.
Describe the job ›
How it keeps going

Regular catch-ups, and someone to ring in between.

The part that makes it stick

Training that ends on the last day of training does not survive contact with a busy month. What makes the difference is a standing session in the calendar that somebody has to bring work to. It is the same reason a gym membership is not the same thing as a training partner.

Every fortnight or every month

The catch-up

A working session with the people actually building. What is running, what it cost, what broke, what to try next, and what to stop. It is a review of real output, not a status update, and it is where most of the learning lands.

Cadence set with you at the start, and changed when it stops fitting.
When the question is bigger

Consulting on call

Some decisions do not wait for the next catch-up. A vendor changes its terms, a tender asks where your data is processed, someone wants to point an agent at the finance folder. You get somebody to think it through with, before rather than after.

Included hours in the programme, and hourly beyond them at the published rate.
Every quarter

The honest review

Licensing against actual usage, spend against what it returned, and whether the framework still matches how people are really working. This is the session where things get switched off, which is a good outcome and a rare one.

Part of the programme, reported in writing so you can hand it to a board.
Where this overlaps with a plan. If you would rather we ran the automations ourselves and simply reported on them, that is a monthly AI plan and it is already priced. This programme is the other choice: your people do the building, we teach and review. Plenty of businesses run both, with us managing the things that must not break and the team experimenting with everything else.
The whole bill

Three layers, and only one of them is ours.

Nothing hidden in the middle

Most AI quotes fail because they price the engagement and go quiet about the running cost. There are three separate layers here and they behave differently. We itemise all three, including the ones that are not ours to charge for, and teaching your team to read them is itself part of workstreams two and three.

Layer 01

The platform

Per seat or per pack

Paid to Microsoft, Anthropic, OpenAI or whoever else, mostly monthly and mostly per seat. Predictable, and the easiest layer to over-buy. Microsoft bills this in New Zealand dollars; most of the others bill in US dollars, so that part of the bill moves with the exchange rate. We will tell you when you are paying for seats nobody is using.

Layer 02

The usage

Per token or per credit

The one that varies, because it follows how hard the work is. This is the layer people are surprised by, so it gets a ceiling set at build time and a monthly figure you can see rather than infer. Keeping it down is a skill, and it is one your team leaves with.

Layer 03

The programme

Fixed before we start

Ours, and the only layer on this page we set. Fixed in writing before anything begins, with the cadence and the number of people named in it, so there is nothing to discover later.

We have not published a price for the programme, on purpose.

Priced per business, because it depends on how many people take part, how often you want us there, and how much of the building you want to do yourselves. Ask and we will give you a number, not a range. What we will not do is print a headline figure that has to be padded to be safe, then quietly requote once we understand the job. Tell us the shape of your team and you will get a fixed number in writing.

Ask for a number ›
One thing worth saying plainly. AI work is not covered by a general IT support agreement. Not by a per-user plan, not by a per-device plan, not by a site fee. Training your team, building agents, running them, fixing them and answering questions about them sits under an AI plan or this programme, or is billed as time, and that is deliberate rather than an oversight. It keeps the cost of AI visible to the person paying for it instead of buried in a support line that was never priced for it.
Start it

Tell us who you want building.

We reply within one business hour
Step 1
A short call, no charge
Enough to work out which of the six workstreams you are actually short on, and whether a programme is even the right shape for you.
Step 2
A fixed number, in writing
Scope, cadence and the people taking part, priced before anything starts.
Step 3
Your team builds the first one
One job, one data source, one person using it, with us next to them rather than in front of them.

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Or, much faster

One idea, one call.

If you already know the job and just want a straight answer on whether it is worth building, this is the shorter road. Two fields and the idea. We will come back with a yes, a no, or the cheaper thing you should do instead. No obligation and no sequence of follow-up emails.

Straight answers

Programme questions, answered.

FAQ

Priced per business, because it depends on how many people take part, how often you want us there, and how much of the building you want to do yourselves. Ask and we will give you a number, not a range. What you will get back is a fixed number in writing, with the cadence and the number of people named in it, before anything starts.

Sometimes you should just pay us to build it, and we will say so. A single well-defined system that has to work and rarely changes is a scoped build. The programme is the better answer when the opportunity is spread across the business rather than concentrated in one place, because the people who know where the wasted hours are will always spot more of them than we will. It also removes the dependency, which is worth something the first time a vendor changes its terms.

The people who do the repetitive work, not only the technical ones. The best builds we have seen came from a finance manager and an operations coordinator, because they knew which fifty minutes a day were being wasted. You want somebody technical in the room for the plumbing and the permissions, but if the group is entirely IT, the ideas tend to be about IT.

The first small build usually happens in the first few sessions, because we deliberately pick a job that is narrow enough to finish. The framework and the licensing work runs alongside it rather than in front of it, with one exception: if the first idea touches your document estate or Microsoft 365 data, readiness comes first, because an agent inherits whatever over-sharing is already there.

On business and enterprise tiers, generally not by default, and that is one of the real reasons to move a team off personal accounts onto a business plan. The important part is that this is a contractual question with a written answer per vendor and per tier, so it belongs in your framework rather than in a reassurance. We will show you the terms rather than summarise them, and teaching your team to check that for themselves is part of workstream one.

Mostly your team can, once they know what drives it. The biggest savings come from sending less rather than switching vendor: retrieving the pages that matter instead of the whole library, using a cheaper model for the work that does not need judgement, caching the part of a prompt that never changes, and batching anything that is not urgent. We set a ceiling at build time and report cost per run, so an expensive agent is visible rather than absorbed.

Usually not, but it is a fair question and it gets a real answer rather than a reflex. The cases where it genuinely wins are data that is not permitted to leave your control, a regulator or tender wanting a straight answer on residency, or volume high enough that per-token pricing stops making sense. Below roughly 2 million tokens a day an API is normally cheaper than the hardware before anyone is paid to look after it. If the answer does turn out to be yes, we run sovereign hosting in New Zealand.

Models are replaced regularly and the good ones behave slightly differently when they are. An agent built as a single enormous instruction tends to break quietly at that point. Built properly, with the job broken into checkable steps, moving to a newer model is a test run rather than a rebuild. Knowing that difference is one of the things the programme exists to teach, and the catch-ups are where it gets caught.

No, and that is deliberate. General support agreements, whether per user, per device or per site, exclude AI tooling, agents and automations. AI work sits under this programme, under an AI plan, or is billed as time. The reason is honesty about cost: absorbing AI support into a plan that was never priced for it hides a growing bill inside a line item you thought you understood.

Pick one job.
Let your own people build it.

The businesses getting value out of AI did not start with a strategy. They started with one annoying, repetitive job, a person who was glad to see the back of it, and somebody in the room who knew what to watch out for.

And relax

Getting started is the easy part.

Onboarding without drama

We do the switch: your current provider, the migration, the handover, all of it. Most teams barely notice the cutover happened.

Everything looked after

On the right plan, compliance, reporting and budgets are handled inside the partnership. You run the business; we run the IT underneath it.

Your QBR writes itself

Quarterly business reviews are generated automatically from your live environment: spend, posture, recommendations and roadmap, ready for the board, reviewed with your account manager.

The honest bit: the full looked-after experience comes with the right plan. We charge fairly for what we take on, and when costs step up it's because you are taking on more, always moving in the right direction.

Sovereign by design

New Zealand owned and operated.

Sovereign data centres across New Zealand and Australia, with your data kept onshore wherever it's required. Our team understands New Zealand, and our leaders have built, scaled and secured businesses right across the New Zealand landscape.

Sovereign data centres · New Zealand & Australia
  • Auckland
  • Christchurch
  • Sydney
  • Melbourne
  • Brisbane
  • Perth
International data-centre operations
  • Singapore
  • Germany
  • Netherlands
  • USA

Servers available in minutes, not days.

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Accreditation

Microsoft Solutions Partner in both Modern Work and Security: the two designations covering the platform your business runs on and the security that protects it.

Microsoft Solutions Partner, Modern Work Microsoft Solutions Partner, Security
Fortinet Partner Veeam Partner Lenovo Partner HP Partner SentinelOne Partner Microsoft Azure Microsoft Copilot Claude
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