Frontier-class
AI, on your floor.~$25K turnkey.
The specialty: a small office running frontier-class local AI — private, fast, and fully owned. No cloud lease, no token meter, no vendor reading your documents. One machine in the corner, tuned to the way your business actually works. Text, images, video, even 3D — generated locally, with no per-asset bill.
Renting gets
expensive.
Cloud AI is easy to start and impossible to leave. You wire it into every workflow, then the token price moves — and you have no say. Millions of dollars a year, decided in someone else's boardroom.
Then there's the part most offices only notice too late: your data goes with the tokens. Client files, medical notes, contracts, payroll. It leaves the building, lands on infrastructure you don't control, and lives under terms you didn't write.
And when the model is the product, your data is the raw material. Local AI ends both problems at once — the meter and the exposure.
One office.
One rack.
Zero tokens.
Turnkey means turnkey: I survey the work, spec and rack the hardware, load frontier-class open models, tune them on your own documents and voice, wire them into the tools your team already uses, train the staff, and stay on to keep it running.
You own the machine. You own the data. Your recurring cost is maintenance, not a metered pipe to a datacenter.
- Hardware, spec'd and racked — sized to your concurrency and context needs
- Frontier-class open models — served locally at interactive speed
- Your corpus, tuned in — proposals, manuals, policies, customer history
- Integration — chat, document Q&A, drafting, phone/voice, internal search
- Privacy by architecture — inference stays on-premise; nothing egresses
- Staff onboarding — the team actually uses it
- Managed care — monitoring, updates, model refreshes, backups
- Unlimited generation — images, video, brand assets, 3D — no per-file fees
Unlimited
images. Film.
Objects.
The same box does more than answer questions. Because the models run on your hardware, generation stops being a meter. Photos, video, brand assets, product renders, textures — make as many as the work needs, at no cost per image and no cost per second.
It reaches into 3D, too: concept drafts, mockups, and printable designs. Where a cloud subscription charges every time you iterate, here iteration is free — so you actually explore instead of settling for the first try.
- Photo & image generation — unlimited, on your own machine
- Video & motion — generate and re-generate with no per-second fee
- Brand & marketing assets — logos, layouts, social, ad variants
- Product & concept renders — iterate until it's right
- 3D design & modeling — drafts and printable files from a prompt
- No watermarks — what you make is yours, in full
Not a toy model
in a shoebox.
The gap most people know is the gap between a chatbot and a real assistant. Closing it takes the right tier of open model, the right serving stack, and enough memory and bandwidth to hold your context without choking. That's the engineering.
| Dimension | Home-office chatbot | Snail3D install |
|---|---|---|
| Model tier | small / quantized hard | frontier-class open weights |
| Speed | slow, single stream | interactive, multi-user |
| Context | a few pages | whole manuals, long conversations |
| Your data | leaves the building | never leaves the building |
| Cost | per-token, forever | owned hardware + care |
| Availability | depends on someone's API | works offline, works when they don't |
Survey. Build.
Tune. Hand off.
Two to four weeks for a single office, depending on integration depth. You keep working the whole time.
Survey
What the office actually does all day, what data matters, what it can't send anywhere, and where AI would buy back real hours.
Spec & build
Hardware sized to the workload, racked on-site, the serving stack stood up and benchmarked against your own prompts.
Tune
Open models adapted to your corpus and your voice — retrieval over your documents, tuned prompts, guardrails for the work that matters.
Integrate & train
Wired into the tools the team already touches; staff trained on real tasks, not a demo.
Manage
Monitoring, updates, model refreshes, backups — and a human who answers when something drifts.
Offices with
something to protect.
If your work runs on documents that shouldn't leave the building, or on volume that makes per-token pricing painful, local AI is the better economics — and often the only compliant option. A few that fit especially well:
Based in El Paso, working across the Southwest and remotely. If your industry isn't listed, it's probably still a fit — the question is whether the box pays for itself, and it usually does when you're already spending on token AI.
I have as much
to lose as you do.
I'm a veteran. A Christian. A husband, and a father.
Which is to say: I'm not a stranger with a server farm. I live here in El Paso. I have a family, a name, and a reputation in this town — things I'd fear to lose, and would never trade away for a few dollars of someone else's data.
That's exactly why I build local AI instead of reselling the cloud. I treat your privacy the way I'd want my own family's records treated — because the same promise I make to you is the one I'd want kept for my own household, my church, my kids' school.
When your data stays on a machine in your building, you don't have to take a company's word for it. You can see the machine. And you can look the man who set it up in the eye.
The short
answers.
Is local really as good as the cloud?
For the tasks that run a business — summarizing, drafting, querying documents, extracting, answering phone and chat — frontier-class open models close the gap to within noise of the big cloud models. For the rare task that needs the absolute bleeding edge, we can route it out through an API deliberately, with privacy controls. The point is that the default is local.
Why $25K instead of a monthly bill?
You're buying a machine you keep, not renting capacity you lose. Over a normal office's horizon the install costs less than the token bill it replaces — and at the end you still own the asset, the data, and the workflow.
What's the recurring cost?
Managed care — monitoring, updates, model refreshes, backups, and support. Modest next to per-token spend, and it doesn't rise every time a vendor reprices their API.
What if it breaks?
It's a machine on your floor, so most issues are contained, and I can reach it remotely or come on-site. Offline means outages elsewhere don't take your assistant down with them.
What data do you need from us?
Enough of your real work to tune the model — the manuals, templates, and history that represent your business, with whatever redaction you need. It stays on your hardware.
How do we start?
A short walkthrough call. I'll look at what you run, what you spend, and what you'd want AI to do. If it pays for itself, we scope it. If it doesn't, I'll tell you.