One AI operating system,
for your whole business.
One agent per department, answering in the channels your team already uses. Every figure read from your own systems, every action approved by a person, and the records kept on your infrastructure — not ours.
Watch it work.
Sixty seconds: one question travels four departments, comes back as one answer, and stops for approval before anything leaves the business.
An agent that already knows the work
Accounting, marketing, payroll, operations — each gets its own agent in its own channel, connected to that department’s systems. They never share data with each other, so a gap in one never becomes a leak in another.
Nothing leaves without a person
The agent proposes; your team approves. Every draft email, payment, post and vendor chase sits in the channel with the figures behind it, and every approval is logged with who signed off and when.
The records stay on your server
Business data, agent memory and the Slack bridge run inside a boundary you control. Use hosted frontier models for the hard judgement calls, or run open-source models on your own hardware and close the loop completely.
Why one question takes three people to answer
In most businesses past a certain size, a simple question — “are any invoices slipping?” — has to travel down through a department head, a team lead and an analyst before anyone can answer it, then travel back up the same three layers. Do that across accounting, marketing, payroll and operations and a single morning’s check-in becomes twelve separate handoffs, each one a place the answer can sit for a day, get garbled, or simply get missed.
None of those three layers is doing anything wrong. They exist because someone needs to pull the figures, someone needs to sanity-check them, and someone needs the authority to act on them. The AI operating system does not remove that structure — it collapses the distance it travels, so the same checks happen in seconds inside one conversation instead of across a week of Slack threads and status meetings.
The four agents below are the shape of a standard deployment. Yours are built around the departments and systems you actually run.
Ask once.
One founder, one morning, four departments. Each agent lives in its own channel, already knows that department’s systems, and only speaks up with something worth a decision.
Four agents, one picture — and because they share nothing except the questions you ask them, a mistake or a gap in one department’s agent never touches another’s data.
Every step stays visible.
Follow that invoice chase from end to end. This is the exact sequence every request goes through, every time — nothing happens off to the side where you cannot see it.
Every request starts as a plain question, typed where the work already happens. No new tool to open, no form to fill in.
The agent reads the live figures from your accounting system over a connection you control. The records themselves stay on your infrastructure; only what the task needs is pulled into context.
Which model handles the request is a setting you control, not a lock-in. Route routine drafting to a cheaper or local model, and save hosted frontier models for the judgement calls that need them.
The agent proposes, it does not act. For anything that leaves your business — an email, a payment, a public post — the draft sits in the channel until a person signs off.
One click, visible to the whole team, with a permanent record of who approved what and when — the same audit trail a compliance review or an external auditor would expect to see.
Your data stays on your server.
That same approval you just saw runs on infrastructure you control. Business records, agent memory and the Slack bridge all sit inside a boundary that is yours — your server, your cloud account, your PDPA obligations met by design rather than by a vendor’s promise.
Open-source models — Llama, Qwen, Mistral, DeepSeek among them — can run on your own hardware inside that same boundary, so nothing leaves at all. Hosted APIs like Claude, GPT or Gemini stay available as an option for the judgement calls that benefit from a frontier model; when you use one, only the prompt for that specific task leaves, never your underlying records.
Which route you take is a setting, not a trade-off we make for you.
How it ships.
A standard architecture, deployed in stages, with a working agent on your real data before the second invoice arrives.
Workflow audit
One week inside your operations: which recurring questions cost the most handoffs, which systems hold the answers, and which agents are worth building first. You leave with a worked map, not a sales deck.
Workspace and first agent
We stand up the private workspace, connect the first department’s systems and ship one agent end to end — live in your Slack, with the approval layer and audit log already switched on.
Agents across the business
One department at a time, in two-week cycles. Each agent goes live only when it answers real questions from real records correctly, and your team has used it for a full week.
Yours to run
Documentation, team training and admin handover. The workspace, the integrations and the audit history are your accounts; we stay available for tuning, new agents and model changes.
Packages
Start with one department or make it the operating layer for the company. Every package is fixed-scope and priced after the audit — no per-question metering.
Pilot
- One department, one agent
- Up to two systems connected
- Approval flow and audit log
- Private Slack workspace
- 30 days of tuning
Core
Most common- Up to four departments and agents
- Connections to your existing systems
- Model routing, including local models
- Team training and playbooks
- 90 days of tuning, then quarterly review
Company
- Company-wide agent rollout
- Custom agents and cross-team workflows
- SSO, retention and audit export
- Dedicated engineer and on-site workshop
- Model and vendor review each quarter
Questions
What exactly do we receive?
A running system, not a slide deck: a private workspace with one agent per department, the approval layer and audit log, connections to your existing systems, documentation, and a trained team. The accounts and the data are yours.
Is this a product we buy, or something you build for us?
Both. The AI Operating System is a productised deployment — the same architecture every time — configured around the systems and workflows you already run. You choose a package; the audit decides what goes in it.
Where does it run?
On infrastructure you control — your server or cloud account — with a Slack workspace as the interface. We can also host it for you during a pilot if you would rather not provision anything before you see it working.
Do we have to use Slack?
Slack is the interface today because the work already happens in channels, and approvals need to be visible where your team is. Microsoft Teams deployments are available on request.
Which systems can the agents read?
Anything with an API or a database we can reach: accounting and payroll platforms, Google Workspace or Microsoft 365, your CRM, e-commerce and payments, shared drives, and internal databases. If a system has no API, we can usually automate its export.
What happens if an agent gets something wrong?
Nothing leaves your business on an agent’s word alone. Every proposed action sits in its channel, visible to your team, until a person approves it — and the log records what the agent saw and what was approved.
Do we have to use open-source models?
No. Open-source, self-hosted models are one option for teams that want data to never leave their own hardware. Hosted frontier models remain available and are often the better choice for harder judgement calls — you can mix both.
How long until it is live, and what does it cost?
The first agent is usually live within two weeks of the audit, and a four-department rollout takes six to eight. Price depends on the number of departments, systems and the level of support you want — it is fixed in the proposal after the audit, not metered per question.
Book Your Free
AI Audit
We'll spend 30 minutes learning about your operations, then tell you exactly where AI can move the needle — and where it can't. No commitment required.
We take on a limited number of engagements each quarter. If AI isn't the right fit for where you are right now, we'll tell you that too.