You're paying for AI your team barely use.
We build the skills and architecture around the workflows your team already use, so the tools you pay for start earning their keep.
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10 structured insights on this week's usage
Operations: strong skill uptake, light on context reuse.
Actionable: add pricing rules to the quote skill.
What we actually build
We do not just prompt agents. We build the harness around the agents your team already use, so we can govern who sees what, ground them in your real data and workflows and keep them working when the models change.
- Skill filesA folder, not a saved prompt. The job, how your business does it, and the templates and rules it reads from.
- Context filesWhat the model cannot know: your products, your pricing logic, your terminology, your tone. Every skill reads from them.
- Role designWhich skills and context each person gets, so everyone opens the tool already set up for their job.
- Role-based access controlWhat the assistant can reach, not just what it can do. Permissions per person, so finance data stays with finance.
- The harnessAll of it wired over your own Claude or Microsoft organisation. Models change; the harness keeps working.
Govern · Monitor · Optimise
Built in weeks. Run for years.
The harness going in is the start, not the finish. An AI Operating System is run: everything on a register, usage and cost measured on one set of axes, access governed per role, and the spend optimised on evidence. 94 percent of enterprises say they are concerned about AI sprawl and only 12 percent have a platform to manage it. This is that layer, sized for a business without a platform team.
No agent acts alone. Every action that changes the business waits for a human. Every agent can be stopped instantly.
Your team does the work. Sentry stands watch.
Register
Every skill, assistant and agent the business runs goes on one register: what it is, who owns it, and what it is allowed to touch. Including the ones that arrived inside other software.
Monitor
Usage, adoption and cost tracked on one set of axes: who is driving the tools, which skills earn their keep, and what each workflow actually costs to run.
Govern
Role-based access control on top of your existing directory, consequential actions held for a human before they run, and an audit trail of who approved what.
Optimise
Context re-orchestration, model routing and token tracking, so the same work runs at a fraction of the spend. Every recommendation backed by the system's own numbers.
Semantic model routing
Each request routed to the model that handles it best. Usually the largest saving.
Context re-orchestration
Each call carries only what it needs, not the whole history.
API orchestration tuning
Tool calls parallelised: twenty seconds down to two.
Knowledge base restructuring
Retrieval answers in one hop instead of five.
Conversation-level token tracking
A cost regression is visible the day it appears.
Security · Sovereignty · IP
Your data stays yours. The harness becomes your IP.
Everything we build is documentation of how your business actually works: your processes, your pricing logic, your terminology, and who is allowed to reach what. Written down, versioned and owned by you, in your tenant. Models will change and staff will move on; the operating system keeps compounding. Competitors can buy the same licences. They cannot buy the architecture built around how your team works.
Our wider security posture lives in the Trust Centre.
Your organisation, not ours
Built over your own Claude, ChatGPT, Copilot or Gemini organisation. The licences, the data and the harness all live in your tenant, and revoking our access takes a minute.
Nothing installed
No software lands on your infrastructure. We work through the admin surfaces your vendors already provide, with credentials issued by you and revocable by you.
Read-only by default
Credentials are read-scoped. The only write path is the one you choose to arm: the approval gate, which holds an action until a person allows it.
Your region, when it matters
Where sovereignty is the deciding factor we route inference inside your boundary. For a medical network we sent it through a custom gateway to AWS Bedrock, so patient data never left the region.
Teams we have deployed this on
An organic baby brand had Claude, and no real way to use it.
A merchandising process ate a full day every week. We built a Claude coworker layer over their existing SharePoint, and more than ten people now query live data in plain English.
Frontier AI in front of clinical staff, without the data leaving the country.
Fifteen practices rolled out Claude Desktop from admin to board, with inference routed to AWS Bedrock so patient data never leaves the region.
A sales team's booking grind, handed to an AI SDR.
We built a Simulator that cut new-rep ramp from three months to one, then trained an AI SDR on that data. It calls every Meta lead within about five minutes.
Questions we get asked
What is an AI Operating System?
The layer we build and run over the AI your business already pays for: the skill files, context files and role design that make the tools genuinely useful, plus the register, monitoring, governance and optimisation that keep them safe and worth the spend. It lives on your own Claude, ChatGPT, Copilot or Gemini organisation and it is owned by you.
Our team is not technical. Is that a blocker?
No, that is the starting point. Every rollout we run assumes no internal AI capability and non-technical staff. The work is building the harness so people do not need technical skill to get value: they open the tool and their role is already set up for the job they do.
How is this different from an AI training course?
A course teaches people to prompt and leaves. We build the skills, context files and role design over your own organisation, so the value is in the system rather than in what somebody remembered from a session. Training alone does not survive contact with a busy week.
We tried ChatGPT and it never stuck. Why would this be different?
Because nothing was built. Without context files the model does not know your business, and without role design everyone starts from a blank box and gets a different answer. Adoption fails for structural reasons, not because people lacked enthusiasm.
Which AI tools do you work across?
Claude, ChatGPT, Microsoft Copilot and Google Gemini. We work with whatever you already pay for rather than moving you onto something new, and we will tell you when a licence you are holding is not worth renewing.
How long before we see hours back?
The harness goes in within the first couple of weeks, and that is usually where the first hours appear. The larger gains come from the return visit, once we can see what people actually adopted and build around it.
How much of our team's time does it cost?
Short sessions per team rather than days out of the business. We are watching the work, not running a classroom, so most of the effort sits with us.
Can we control what each person's assistant can reach?
Yes, through role-based access control. Permissions are set per person on top of your existing directory, so the assistant only reaches what that role is allowed to see. It is the difference between handing a team a powerful tool and handing them the whole filing cabinet.
How are risky AI actions controlled?
Nothing that changes the business, a payment, an outbound email, a record update, happens without a human approving it first. Consequential actions are held in an approval queue, permissions are enforced per role, and an audit trail records who approved what.
Is this software we have to staff ourselves?
No. It is delivered as a managed service: live in weeks rather than quarters, with a named Sentry team who monitor the estate, curate the optimisations and meet you on a regular cadence.
Does our data stay private?
It can stay fully in region. For a medical client we routed inference through a custom LLM gateway to AWS Bedrock, so patient data never left their boundary. Where sovereignty is the deciding factor we build the infrastructure to match.
Do you work with businesses outside Auckland?
Yes. We are Auckland based and run rollouts across New Zealand and Australia, on-site or remotely.
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