Private AI · For Business

Your data
stays on
your machine.

FactoryOS delivers fully private, on-premise AI to the firms that hold other people's secrets — medical practices, law and accounting offices, wealth managers — without the complexity. I handle the hardware, the software, and the setup. You just use it.

HIPAA Ready GDPR Ready No Cloud Required Air-Gap Compatible Data Never Leaves
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Data Channels

You decide who sees what —
the system enforces it.

Your company's data lives in channels you control. Whoever you put in charge of permissions sets which people reach which channel — so ops can't open HR, a new hire can't read the CFO, and a client's files stay with the team on the account. Default-deny, a private channel for every person, your org chart deciding access instead of a policy binder. The walls aren't a rule you hope people follow — they're how the system is built.

What It Does

Useful the day it ships —
before a line of custom code.

Personal Assistant

Walk in prepared, every day

Daily briefings and per-meeting briefs are assembled overnight from your calendar, inbox, tasks, and the people you're about to meet — so you start informed instead of catching up.

Private Chat Assistant

Chat with your own data

From day one, FactoryOS ingests your company's files and lets your team ask questions of them in plain language — answered from your own documents, on your own hardware, never sent anywhere.

Knowledge Graph & Retrieval

Answers from across your data

A temporal knowledge graph and a stacked retrieval engine — keyword, vector, fusion, and reranking — surface the connections a plain search throws away, including ones no single document states.

Workflows & Human-in-the-Loop

Automate the work, keep the judgment

Build workflows by dragging and dropping cards, then drop an approval gate where consequences live. The agent gathers, reasons, and proposes; a person sees the justification and makes the call.

Agentic Browser

Research the live web, unblocked

A real Chrome the AI drives like a person — from your own connection, not a flagged data-center IP — folding what it finds into the same knowledge base as your private files.

Voice

Dictate even the sensitive things

Speech-to-text and text-to-speech run on the same box that holds your data, so a clinician's note or a privileged call is transcribed in place and the audio never leaves the building.

Channels & Permissions

Need-to-know, enforced by design

Data is split into channels so ops can't see HR and HR can't see ops, with default-deny permissions and a private channel for every user. Least privilege lives in the architecture, not a policy binder.

Brain Page

See everything it knows

An interactive graph of every person, project, and relationship in your second brain. Click any node to trace how you know someone, and through whom, in seconds rather than an afternoon of digging.

Persona Studio

An assistant you want to use

Shape a local AI character by chatting it into existence, then place it in scenes that fit your day, season, and news — all generated on your own hardware, nothing sent out.

Why It Matters

Some businesses can't afford
to share their data with anyone.

Compliance by Architecture

HIPAA, GDPR, and similar regulations require strict data control. When AI runs locally, patient records, client files, and operational data never touch an external server — compliance becomes structural, not procedural.

No Cloud Vendor Risk

Cloud AI providers change their terms, raise prices, get breached, or shut down. Your local system keeps running regardless — no vendor dependency, no surprise policy updates, no service disruptions you don't control.

Dedicated, Not Shared

Cloud AI is shared infrastructure that can throttle you when other customers spike. This machine serves only your office — no external rate limits and no per-token meter. At true peak, your own heavy demand becomes a brief queue for the GPU: a graceful delay, never a crash or a surprise bill.

Own What You Build

Prompts, outputs, and everything your business generates stays on your hardware, under your control. There is no ambiguity about data ownership when the machine is in your office.

Not An App — A Platform

Useful on day one.
Built to build on.

It arrives working, not empty — FactoryOS ingests your company's data and your team chats with it securely from the start. The bigger upside comes from custom tools built on the same foundation: think Linux for AI, where ingestion, retrieval, GPU scheduling, permissions, and the knowledge graph are already wired, so what you build next is mostly configuration rather than a year-long project.

Useful out of the box

Point it at your files and the office is chatting with them on day one. The base system is already a capable, fully private assistant over everything your company knows.

Where the upside compounds

Custom tools on top reuse the same wired foundation, so each one ships faster than the last and the cost spreads across all of them — the opposite of buying ten disconnected apps.

No per-seat licensing

You buy the hardware and the software that runs it, not seats. Put the whole office on your own install; people cost shared GPU time, which at peak means a queue, never a per-user fee.

How I Use It

I start the day caught up,
not catching up.

Most mornings, it's already been working. Overnight it keeps an eye on the things I care about and lines up whatever needs my okay — each with a plain note on why, and the actual data behind it. I read down the list with my coffee, approve what's right, wave off what isn't, and the busywork is mostly handled before the day starts. It never makes the call for me. It just makes sure I'm never the bottleneck.

⚠ Pending Task Approvals 2

The following operations were queued by agents and require your approval before proceeding.

🤖 Agent Decisioncalendar Jun 18, 2026 6:39 AM
Your 2:00 collides with the Hartwell call, which has run long before. Proposes shifting it to 3:30 — both invitees are free then.
Request data 
{
  "operation": "reschedule_event",
  "event": "Weekly review",
  "from": "14:00",
  "to": "15:30",
  "invitees_free": true,
  "channel": "calendar"
}
↺ Crawlresearch Jun 18, 2026 6:34 AM
A topic you track published new guidance overnight. The agent gathered four sources and wants to fold them into the research channel.
Request data 
{
  "operation": "crawl",
  "topic": "HIPAA guidance for AI vendors",
  "pages": 4,
  "writes_to": "knowledge_graph",
  "channel": "research"
}
An example of the in-app approval queue.
How It Works

You tell me what you need.
I handle the rest.

01 · Consult

We talk

I interview you to understand your workflows, compliance requirements, and what you actually need AI to do for your business.

02 · Specify

Right-size the solution

Based on your needs, I determine the correct hardware spec and software configuration — no more than necessary, nothing left out.

03 · Source

I get the hardware

I procure the machine on your behalf. You don't need to know what any of it means — that's my job.

04 · Configure

Loaded and tested

FactoryOS goes on. Models are selected and loaded. Basic integration with your systems is validated before it leaves my hands.

05 · Ship

Plug it in

The machine arrives ready to run. You plug it in and start using it. I remain available for questions and future changes.

The Offer

Everything included.
Where it all starts.

FactoryOS Private AI Office

My standard-sized solution, and the smallest package I offer — built for a firm stepping into private AI. Hardware, software, and hands-on integration, all done for you, shipped to your door, ready to run from day one. The same machine comfortably serves an entire office — far more people than its size suggests, because they never all query at once — so most firms never outgrow it.

$50k
All-in · One-time · Standard solution
Hardware
NVIDIA DGX Spark
Compact, powerful, purpose-built for local AI inference. Fits on a desk. Runs serious workloads.
Software
FactoryOS
The operating layer that runs your models, manages your tasks, and keeps everything private and on-device.
Service
Setup & Integration
Consultation, configuration, and basic integration into your existing systems — done before the machine ships.
Every engagement starts with a needs interview. Like any considered purchase, you don't buy it blind — I map your workflows, compliance needs, and expected concurrency first, so you know where your performance will land before anything ships. Heavier use or specialized work scales up from here on hardware matched to your needs and budget: always a known number, never a surprise bill. The DGX Spark is the reference build — the one place I name specific hardware, because it's where price and spec get real. FactoryOS itself isn't tied to it: it runs on a standard Linux stack and moves onto bigger machines or accelerators as you grow. You're buying the system, not getting locked to a box.
Read Before You Decide

Five areas worth understanding
before any conversation about local AI.

Sovereign Infrastructure Why the hardware has to be yours → Agentic Workflows What an AI OS actually does for your office → Compliance & Privacy HIPAA, privilege, and zero-trust in practice → The Private AI Playbook Buy vs. build, TCO, and the 3-year model → FactoryOS Capabilities, architecture, and governance →
Get in Touch

Let's figure out
what you need.

Every business is different. Send me a message and I'll follow up to schedule a conversation — no sales pitch, just a straightforward discussion about whether local AI makes sense for you and what that looks like.

I work with businesses in medical, legal, logistics, and other compliance-sensitive industries. If your data needs to stay private, we should talk.