Montreal-based · Worldwide Operations

Your AI.
Your Hardware.
Your Data.

On-premise AI infrastructure built for privacy, performance, and independence. We deploy powerful local LLMs on your hardware — zero data leaves your network, zero cloud dependencies, zero compromise.

Explore Services ↓ See Our Setup →
0
Models Running
<200ms
First Token
0
Bytes Leaked
~40t/s
Throughput
What We Do

Full-Stack AI.
Delivered On-Premise.

From single-GPU workstations to multi-node GPU clusters, we architect, deploy, and maintain private AI infrastructure tailored to your compliance, latency, and budget constraints.

💻

GPU Infrastructure

Multi-GPU architecture design. CUDA optimization, VRAM budgeting, Ollama & vLLM deployment on consumer and enterprise hardware.

NVIDIA / AMD
🔒

Private RAG Systems

Knowledge base AI built from your internal documents. HIPAA, SOC2, and GDPR compliant by design. Zero data egress. Ever.

Zero Trust
🔈

Enterprise Integration

AI into Slack, Confluence, Jira, email, wikis. All running on your stack, integrated with your existing workflows and tools.

API / Workflow
🎓

Training & Workshops

Hands-on sessions on model selection, quantization, prompt engineering, and multi-GPU setups. Scale your team's AI literacy.

$750/session
Why On-Premise

The Cloud Alternative.
That Actually Pays Off.

Every dollar spent on cloud inference disappears into a black hole. An on-premise GPU is an asset that compounds for you, in perpetuity.

0

Bytes Leave Your Network

All inference runs locally. Customer data, employee records, proprietary documents — they never touch a third-party server.

$5K+

Monthly Cloud Savings

An RTX 5060 Ti replaces $500–$2,000/month in OpenAI, Claude, or Gemini API costs. ROI in under 2 months.

∞

Requests Per Day

No rate limits. No throttling. No token budget exceeded emails. Your GPU, your rules, your pace.

<200ms

First Token Latency

Local inference eliminates network round trips. Instant responses for interactive applications and real-time workflows.

$ ollama run qwen:32b # Running locally on your GPU — zero latency
Head to Head

Cloud vs On-Premise.
The Truth About TCO.

Everyone tells you cloud is cheaper. The numbers say otherwise.

☁ Big Cloud AI 💻 On-Premise GPU
Data Privacy✗ Data leaves your network✓ Zero data egress
Predictable Costs~ Per-token, unpredictable✓ One-time hardware buy
Rate Limits✗ Throttling & daily caps✓ Unlimited inference
Latency~ 200–800ms round-trip✓ <200ms local
Vendor Lock-in✗ Proprietary APIs✓ Open-source models
Compliance~ Shared responsibility✓ Full control (HIPAA, SOC2, GDPR)
Custom Fine-tuning~ Expensive API credits✓ Train on your data
5-Year TCO$45,000–$120,000+$2,000–$15,000
Pricing

Investment That
Compounds Locally.

Transparent pricing. No per-token billing. No surprise cloud invoices at 3 AM. What you see is what you pay.

Starter
Home AI Setup
$299
One-time remote session
  • ✓Hardware assessment & GPU compatibility
  • ✓Ollama install & multi-GPU config
  • ✓Model selection & quantization guide
  • ✓Quick-start documentation
  • ✓30 min post-setup support
Get Started
Most Popular
Business
Private AI Deploy
$3,500
$2,500 – $5,000 based on scope
  • ✓Full architecture assessment
  • ✓On-premise GPU deployment
  • ✓Private RAG knowledge base
  • ✓Staff onboarding session
  • ✓Security audit & compliance note
  • ✓30 days post-deploy support
Book Discovery
Enterprise
Full Integration
$11,500+
$8K–$15K + $1,500/mo retainer
  • ✓Multi-node GPU cluster design
  • ✓Production TensorRT-LLM deployment
  • ✓Custom fine-tuning on company data
  • ✓Integration with existing tools
  • ✓Infrastructure-as-code deployment
  • ✓24/7 SLA-backed support
Contact Sales
Live Proof

Our Own Setup.
The Demo That Sells The Service.

"I run 11 large language models on two consumer-grade NVIDIA graphics cards. One is a 2080 Ti that costs $200 used today. The other is a 5060 Ti. Total hardware investment: under $700. I can deploy your AI in one day."

This is the actual workstation that powers our own AI assistant. Dual-GPU, 27.5 GB combined VRAM, running models like qwen:32b at interactive speeds with zero data leaving the machine. This is what your company can run too.

$ nvidia-smi | grep GPU
GPU 0: RTX 5060 Ti (16GB) — Idle
GPU 1: RTX 2080 Ti (11GB) — 75% @ 40t/s
0
Models Running
27.5 GB
Combined VRAM
<$700
Hardware Cost
~$15K
Annual Savings
0 bytes
Data Egress
<200ms
Latency
Industries Served

Privacy-First AI.
For Every Regulated Sector.

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Healthcare
💰
Finance
🐢
Legal
🏗
Manufacturing
🏛
Government
🎓
Education
By The Numbers

Real Infrastructure.
Real Results.

💻
0
GPU Deployments
🌐
0
Models Live
⚡
<200ms
Avg Latency
🔐
0 bytes
Data Egress
💰
$15K+
Client Savings/yr
🛠
100%
Uptime SLA
Process

From Discovery to
Deployment in Days.

A proven four-step workflow refined across client deployments. No guesswork, no rework.

1

Discovery Call

We learn about your data, compliance needs, team size, and AI goals. 30 minutes, no commitment required. You walk away with clarity either way.

2

Architecture Design

We design the optimal GPU setup, model selection, and infrastructure. VRAM budgeting, quantization strategy, and compliance alignment all mapped out.

3

Deployment & Optimization

We install, configure, and tune. Multi-GPU setup, RAG pipeline, integrations, the whole stack. Remote or on-site — your preference.

4

Training & Handoff

Your team learns to use and maintain the system. Full documentation, video recordings, and ongoing support included. You own it from day one.

ROI Calculator

See Your Savings.
In Real Numbers.

Plug in your current cloud AI spend and GPU budget. We'll show you the math behind going on-premise.

📊 Your Numbers

Adjust the sliders to match your situation

$1500/mo
$2000
2

📈 Results

Your personalized on-premise ROI breakdown

🫂

Adjust your numbers above and hit calculate to see your personalized savings breakdown.

FAQ

Common Questions.
Straight Answers.

Any NVIDIA GPU with 8GB+ VRAM works for 7B–14B models. An RTX 5060 Ti (16GB) handles 32B models at interactive speeds and costs ~$450. For multi-node production setups, we design around your budget — from single-GPU workstations to RTX 5090 clusters. AMD is an option but NVIDIA CUDA is the current sweet spot.
OpenAI and Anthropic are great for prototyping but expensive at scale and leak your data. On-premise LLMs like Qwen, Llama, or Gemma give you comparable quality on your own hardware. Your data never leaves your network, your costs are predictable, and you own the infrastructure forever. For most businesses, local 32B models outperform gpt-3.5-class APIs on domain-specific tasks after fine-tuning.
Yes — we deploy via remote session. We'll SSH into your machine, set up the full stack, test it, and hand you a running system. On-site visits are available in Montreal and for enterprise projects. All remote setups include a walkthrough call so your team understands what's running.
A consumer GPU draws ~150–300W during inference. At US$0.13/kWh, that's roughly $13–$26/month for 24/7 use. Even at double that, you're still far below $500–$5,000/month in cloud API costs. Our ROI calculator does the exact math for your situation.
Absolutely. Many clients run a hybrid setup — sensitive data stays on-prem while they use cloud APIs for general-purpose tasks. We can architect your stack so private RAG and internal data processing stays local while non-sensitive work goes to cloud cost-effectively.
A single-GPU setup is done in one session (2–4 hours). Full enterprise deployments with multi-GPU clusters, RAG pipelines, and integrations typically take 1–2 weeks from discovery. We include documentation, recordings, and team training in every package.
Every package includes post-deploy support (30 min for Starter, 30 days for Business). Enterprise plans include a $1,500/month retainer with SLA-backed uptime and priority support. We also offer á la carte upgrades and model switching as new releases come out.
On-premise inherently supports all compliance frameworks — HIPAA, SOC2, GDPR, PCI-DSS, HITRUST — because you control where the data lives. We include a compliance alignment document with every Business and Enterprise deployment that maps your setup to the specific requirements of your industry.
Let's Talk

Ready to Own Your
AI Infrastructure?

Whether you're a homelab enthusiast or an enterprise leader, we have a package that fits. Drop us a line — we respond within 24 hours.

🎓Montreal, Quebec
📱Worldwide Remote
📅Response <24hrs