Built by the engineer on call.

Engineer-led · owner-operated

A Garnet is specified, built and handed over by the same person you talk to. No staff augmentation tier, no account-manager wall — the engineering decision and the customer conversation are the same conversation.

Design my Garnet →Watch it build →

Founder and principal engineer. An M.S. in Customer Intelligence & Analytics and a B.S. in Finance & Computer Science, both from Pace University. The working background is enterprise: Dynamics 365 Finance & Operations, Azure, Power BI and applied machine learning, including multi-million-dollar ERP implementations for Fortune 500 supply chains.

That history is the reason this product is shaped the way it is. Big systems are rarely lost in the build. They are lost at the handover — to people who did not design them, through a vendor who answers to a queue. A Garnet is deliberately the other arrangement.

Scoping, specification, build and handover are one person’s work, so nothing is translated through an account manager on the way to you. While we scope and build, what we see is the conversation with you and any sample material you deliberately share — and that is destroyed on handover. Afterwards the system is beyond our reach: help happens when you invite it, and ends when the work does.

The full version of that promise, including what it does not cover: what we can and can’t see →

The plan was written by a language model running on a machine we own, reached over a local proxy that talks to our own machines alone. The image was rendered by an image model on that same machine. Both were produced once and are replayed here, and we would rather say so than dress a cached file up as something happening in the moment.

That is a deliberate choice. Putting a public button in front of a private model means handing an anonymous visitor an open-ended claim on it. The whole proposition we sell is that your model answers to you alone — running ours as a free service for the internet would be a strange way to demonstrate it.

What the demo is honestly evidence of: these models run on ordinary hardware we control, where every request stays inside the building — which is the same arrangement we install for you, on your hardware, in your building.

A five-step sketch is a shape; a system is the rest of it. A commissioned build is where the specifics live, and they are mostly the unglamorous ones:

• Your material, indexed. The demo works from an example. A build starts by taking your actual documents, mail, drawings or photographs and making them retrievable on your own machine — which is most of the work and all of the value.
• The hardware call. Which machine, and how much of it. That answer comes from your material and your people rather than from a preset. Joining several of your existing machines into one system with Garnet Mesh is a later question: Mesh is in build — the services are written and installed on the reference machine and are yet to be started in service — so a build today is single-machine Garnet, and the second machine can wait.
• The sealed posture. Air-gapped where it should be, telemetry off, the machine quiet, and our access ending the moment it becomes yours.
• Handover. People outside engineering have to be able to use it on a Tuesday, unaided. That is a design problem, and it is the one most private-AI projects lose on.

Design my Garnet →

Rather read than click? Walk the whole build in plain language →