1.
Local inference · Sovereign AI · Zero cloud

ANY1 can run state-of-the-art AI on-prem

We design AI systems and deploy them on hardware you own — Mac Mini, NVIDIA Jetson, DGX Spark. Real-time voice, vision and reasoning that runs inside your walls. Your data never leaves the building.

0%
Data egress
0ms
Voice latency
24/7
On-prem uptime
Per-token cloud fees
01 — The perimeter

Your models.
Your machines.
Your walls.

Cloud AI ships your most sensitive data to someone else's datacenter and bills you forever for the privilege. We flip it: the model lives on a box on your network. Nothing crosses the perimeter, and the cost stops at the hardware.

  • 01
    Nothing leaves the building
    Patient records, formulas, call audio — processed locally, never uploaded.
  • 02
    Pay once, not per token
    Fixed hardware cost replaces metered API bills that scale with success.
  • 03
    Works air-gapped
    Deploys with zero internet dependency — built for regulated and offline sites.
  • 04
    You own the stack
    No vendor lock-in. The weights, the pipeline and the box are yours to keep.
02 — Inference platforms

Hardware sized
to the job

From a silent Mac Mini under a reception desk to a DGX Spark crunching multimodal models, we match the right inference box to your workload, footprint and budget.

Spec my deployment
Apple Silicon01

Mac Mini M-Series

Whisper-quiet desktop inference. Ideal for voice bots, RAG and small-team copilots that need to sit invisibly in an office.
Unified memory up to 64GB
Footprint Palm-sized
Best for Voice · RAG
NVIDIA02

Jetson Orin

Rugged edge AI for cameras, kiosks and machines. Computer vision and wake-word voice at the point of action, no rack required.
Compute up to 275 TOPS
Power 15–60W
Best for Edge vision
NVIDIA03

DGX Spark

A desktop AI supercomputer. Runs large language and multimodal models locally for teams that need serious throughput on-site.
Unified memory 128GB
Model size 200B params
Best for Local LLM
Custom build04

RTX Workstations & Racks

Multi-GPU servers for high-concurrency call centres and vision fleets. Scale from one model to a building full of them.
GPUs 1–8× RTX
Concurrency Hundreds
Best for Scale-out
03 — In production

Voice & vision,
already live

State-of-the-art systems deployed for regulated industries where data can't go to the cloud and downtime isn't an option.

Healthcare

Clinical voice intake bot

Books appointments, triages symptoms and handles patient calls in natural speech — on a box inside the clinic, HIPAA-safe by design.

Live · on-prem
Pharma

Pharma compliance assistant

Answers reps and pharmacists from internal SOPs and drug data via private RAG — auditable, offline, no formula ever leaves the site.

Live · air-gapped
Customer support

Support voice bot

Resolves tier-1 calls end to end with sub-second response, native-language understanding and a clean hand-off to humans when it matters.

Live · 24/7
Security

Face-recognition attendance

4–8 cameras into a single Mac Mini — staff attendance and access logged by face, fully on-site with no cloud video stream.

Deployed
Agriculture

Crop vision & yield AI

Edge models on Jetson read disease, growth and yield straight from field cameras and drones — running where the connectivity isn't.

Field-tested
Knowledge

Private document brain

A searchable, citeable assistant over your contracts, manuals and archives — answers grounded in your files, hosted entirely in-house.

Live · RAG
04 — How the voice stack runs

A full conversation,
start to finish, on one box

Every stage of the voice pipeline — listening, understanding, reasoning and speaking — executes locally. No round-trip to the cloud, no per-minute bill.

01
Listen

Local speech-to-text turns the caller's voice into text in real time.

02
Understand

Intent and context extracted on-device, native to the caller's language.

03
Reason

A private LLM with RAG answers from your own documents and systems.

04
Speak

Neural text-to-speech replies in a natural, human-sounding voice.

05
Act

Books, updates or escalates through your telephony and back-office tools.

05 — Engagement

From idea to on-prem
in four moves

SCOPE

Map the use case

We sit with your team, find the highest-value workflow and pick the model and hardware to match.

BUILD

Engineer the system

Voice, vision or RAG built and tuned on your real data, your terminology, your edge cases.

DEPLOY

Install on-site

The box arrives configured. We rack it, wire it to your network and validate it live.

OWN

Hand over the keys

You own the hardware and the stack. We stay on for support, updates and scale-out.

// Anyone can do it.

Let's put AI
inside your walls

Tell us the workflow you'd hand to a machine. We'll come back with the model, the hardware and a fixed price — running on your premises, not someone else's cloud.