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Custom AI Operating System

A custom AI operating system for your company

Integrate all your data sources, automate your processes, and supercharge every information worker. I build your company its own AI operating system on jet.do, the platform I’ve built and hardened, and make it yours: your systems, your processes, your guardrails, in your own cloud account.

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The problem

Every employee has become the integration layer

Your people already use AI, one browser tab at a time. The model is brilliant; it just can’t see anything. So someone copies a customer’s history out of the CRM, pastes it into a chatbot, and pastes the answer into an email. Fourteen systems, and the AI sees none of them.

Lock it downPeople use personal AI accounts anyway, and customer data leaves through a door you’ll never see.
Open it upConnect everything to everything, let agents auto-approve, and you’ve handed a very confident intern the keys to every system you own.
Another chatbotSame tab, same copy-paste. Nothing changes about what the AI can see or do.
An AI OSOne workspace connected to the systems you already run, with the rules about who can touch what built in.
What it is

An operating system for a company to work with AI

Not an operating system in the Windows sense. One place where your people and their agents work, connected to your data, with guardrails your security team signs off on.

Workspace

It Knows How You Work

Your people ask it to research, write, analyze, or build, and it starts from your context, your vocabulary, and your playbooks instead of a blank page.

Apps

Tools Your Team Builds Itself

Dashboards, trackers, client reports, and decks, built by an agent on request. Each runs in its own sandbox with its own storage and can be shared like a document.

Gatekeepers

Zero Access by Default

A gatekeeper sits in front of each system, narrows access to exactly what was intended, logs every action, and puts anything with side effects in front of a person.

Data

Every Source, One Workspace

CRM, billing, docs, tickets, email, and the line-of-business databases that actually run the company, including the old ones.

Automation

A Human in the Loop

Agents keep working while side-effecting actions queue up. People approve the queue in bulk or one at a time: the speed of auto-approve, the safety of review.

Ownership

Your Account, Any Model

Deployed to your own cloud account, with your choice of AI models, spend tracked by team in one place, and no lock-in.

How it works

Map, connect, automate, hand over

The platform is already built. The engagement goes into the part that’s yours, and it’s the work I’ve done for twenty-five years under other names.

  1. 1
    Map

    Systems & Work

    Every data source, every recurring process, who needs what, and which data is regulated. The same systems map I start every engagement with.

  2. 2
    Connect

    Scoped, Audited Access

    Gatekeepers for Google, Slack, GitHub, and Notion, and custom ones for your CRM, billing, and line-of-business databases, each with the narrowest access that does the job.

  3. 3
    Automate

    Context & Blueprints

    Your vocabulary and playbooks encoded, templates for the work your team repeats every week, and the processes that should run without anyone opening a chat window.

  4. 4
    Hand Over

    Yours to Run

    Model choice and AI spend in one place, logs your security team can read, and a system your team operates without me.

Built on jet.do Guardrails

Security as a property of the system, not a habit

The thing I audit for is the thing the platform enforces.

When I audit apps people built with AI, the findings are rarely about clever code. They’re about access: a key with too much power, a database anyone can query, an integration that can write when it only needed to read. Gatekeepers move that problem from each app to the platform. An agent asked to fix the typos in one Google Doc gets that one doc, not your Drive.

A sandbox around every app and a gate in front of every system is also the first setup where I’m comfortable telling a non-technical team to go build their own tools.

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A gatekeeper, step by step4
01Start with nothingEvery agent and app begins with access to no systems at all
02Narrow the scopeAccess to the one resource someone intended, not the whole system
03Queue side effectsWrites, sends, and deletes wait for a person; the agent keeps working
04Log everythingEvery action recorded where your security team can read it

Company AI setups, judged

  • Customer data pasted into personal AI accountsCritical
  • Agents with org-wide tokens set to auto-approveCritical
  • A company chatbot that can’t see any of your systemsNeeds work
  • A scoped gatekeeper per system, with every action loggedPass
  • Side effects queued for human approval in bulkPass
Who it’s for

Companies whose work is information work

Reading, reconciling, writing, deciding. If your team already pays for AI seats and still copy-pastes all day, this is built for you.

InsuranceAgencies, MGAs, TPAs, and brokers: policy admin, carrier data, commissions, and licensing in one workspace.
Financial servicesReconciliation, reporting, and client servicing across systems that were never designed to talk.
Professional servicesClient reports, proposals, and month-end packages built from the systems where the facts live.
Healthcare operationsEligibility, enrollment, and member operations, designed with regulated data in mind from day one.
Regulated dataScoped access and a full action log help a great deal, but they don’t make you compliant on their own. That’s a design conversation we have before anything gets connected.
FAQ

Questions, answered

How is an AI operating system different from ChatGPT Enterprise or Copilot?
Those give each person a capable assistant. An AI operating system connects that assistant to your own systems through scoped gatekeepers, encodes how your company works, and lets your team build and share its own tools, all inside your cloud account with every action logged.
What is jet.do?
jet.do is the AI operating system platform I build on: a workspace, sandboxed apps, and gatekeepers in front of every connected system. In an engagement I deploy it to your account and customize it for your systems and processes.
Which systems can it connect to?
Everyday tools like Google Workspace, Slack, GitHub, Notion, and Confluence, plus custom gatekeepers for the systems that run your business: your CRM, billing platform, policy admin or line-of-business system, and internal databases, including older ones without modern APIs.
Which AI models does it use?
Your choice. You decide which models are available to which teams, and spend is tracked in one place. You aren’t locked into a single AI vendor.
Where does our data live?
In your own cloud account. The system is deployed there, and your team operates it after hand-over.
Is it safe to let non-technical staff build their own tools?
Safer than the alternative. Every app runs in its own sandbox, and no app or agent can reach a system except through a gatekeeper with narrowly scoped access. Anything with side effects waits for a person to approve it.
Does it make us compliant with HIPAA or other regulations?
Not on its own. Scoped access and a full action log help, but compliance depends on how the system is designed and operated. We work through regulated data before anything gets connected.
How do we start?
Book a free 30-minute call. We’ll talk through your systems, the work your team repeats, and whether an AI operating system fits.
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Give your company its own AI operating system

Book a free 30-minute call. We’ll map where your people lose the most time to copy-paste, and what to connect first.

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