Next-gen enterprise with AI Agents
We help choose hardware and tools—from setup planning to turnkey builds
APPROACH
Hardware is only half
Power without fit is useless—we match the machine to your work
Architecture
Spark or Mac? Memory, speed, and power define the choice
![](data:image/svg+xml,<svg display="block" role="presentation" viewBox="0 0 578 462" xmlns="http://www.w3.org/2000/svg"><path d="M 0 144 L 222 0 L 577.5 162.5 L 325.5 461.5 L 0 245 L 119 0 L 577.5 95.5 L 0 199 L 577.5 419 L 69.5 0 L 119 461.5 L 428 0 L 487.5 461.5" fill="transparent" height="461.5px" id="kMzWo4JtI" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-width="1" stroke="rgba(255, 255, 255, 0.15)" width="577.5px"/></svg>)
Hardware variables
Memory, speed, power, and team size change the answer
Deployment
Local-only or hybrid?
Scale
Solo or team? DIY or turnkey?
Start with the work, not the box
Tell us what you want the machine to do. We will show you the sensible starting path
SOLUTIONS
Cloud plus local compute
Most serious setups are hybrid. Use each side where it wins
Cloud AI
Local machine
Hybrid
Cloud assistants
ChatGPT and Claude are often the fastest way to use frontier AI with zero setup
Fastest
Subscription
Frontier
Hosted
Cloud assistants
ChatGPT and Claude are often the fastest way to use frontier AI with zero setup
Fastest
Subscription
Frontier
Hosted
Local AI machine
Dedicated capacity, open models, and a system you configure around your own work
Open models
Upfront cost
Local data
Your hardware
Local AI machine
Dedicated capacity, open models, and a system you configure around your own work
Open models
Upfront cost
Local data
Your hardware
Hybrid architecture
A local machine adds something different. Keep the cloud, add your own compute
Private local
Search cloud
Best of both
Balanced cost
Hybrid architecture
A local machine adds something different. Keep the cloud, add your own compute
Private local
Search cloud
Best of both
Balanced cost
PRODUCTS
Multiple Products
Covers all major verticals in the tech industry with top intelligence.
Local models
Coding agents
Research and automation
Documents
Image, video and model work
Team AI
Run Local Models
Run open models and private APIs on hardware you control. Keep selected document workflows local when that matters.
Private APIs — Hardware you control
Local Documents — Keep workflows local
Fast Responses — Dedicated capacity
Local models
Coding agents
Research and automation
Documents
Image, video and model work
Team AI
Run Local Models
Run open models and private APIs on hardware you control. Keep selected document workflows local when that matters.
Private APIs — Hardware you control
Local Documents — Keep workflows local
Fast Responses — Dedicated capacity
INTEGRATION
The workload decides the actual machine
We recommend an existing PC, a Mac, a GB10, a workstation, or a team server
STEPS TO USE
3 Steps to Local AI
Tell us what you need to do, and we show a sensible starting path
Describe the work and get a path
Answer short questions to see a recommended hardware class and a rough budget
Tell us who will use the new machine
Explain how local your data must be
Get a starting path without an email
Describe the work and get a path
Answer short questions to see a recommended hardware class and a rough budget
Tell us who will use the new machine
Explain how local your data must be
Get a starting path without an email
Choose the exact level of help
Take the free result, buy a human-reviewed plan, or ask us to configure and build the system
Use the free hardware recommendation.
Get a precise buy list and setup plan
Request a complete hands-on AI build
Choose the exact level of help
Take the free result, buy a human-reviewed plan, or ask us to configure and build the system
Use the free hardware recommendation.
Get a precise buy list and setup plan
Request a complete hands-on AI build
Finish with a clear outcome
Hands-on work is quoted against a written scope, exact acceptance checks and delivery
Secure remote access and autostart
One real end-to-end task passes
Delivery and handover within the UAE
Finish with a clear outcome
Hands-on work is quoted against a written scope, exact acceptance checks and delivery
Secure remote access and autostart
One real end-to-end task passes
Delivery and handover within the UAE
TESTIMONIALS
Trusted by customers
Proven outcomes shared by industry leaders and innovators.
We wanted to deploy AI agents for code review and refactoring, but our security team strictly prohibited sending proprietary code to external APIs. Quant designed a dedicated Team Server for us. Now, our agents interact with repositories locally with near-zero latency, and our source code never leaves our secure perimeter.
Michael V
Lead Software Engineer
We needed a stable and independent architecture for continuous model fine-tuning on specialized tasks. The Quant team deployed a complete AI lab built around two DGX Spark machines. They handled the entire cycle—from hardware sourcing and delivery to environment configuration and turnkey setup
Anna S
Machine Learning Engineer
For processing financial analytics and contracts, a fully private RAG pipeline was critical. Querying open cloud LLMs simply wasn't an option. Quant configured a local workstation that instantly indexes our internal knowledge bases. It provides exactly the uncompromising level of data control we were looking for
David M
Senior Data Scientist
We wanted to deploy AI agents for code review and refactoring, but our security team strictly prohibited sending proprietary code to external APIs. Quant designed a dedicated Team Server for us. Now, our agents interact with repositories locally with near-zero latency, and our source code never leaves our secure perimeter.
Michael V
Lead Software Engineer
We needed a stable and independent architecture for continuous model fine-tuning on specialized tasks. The Quant team deployed a complete AI lab built around two DGX Spark machines. They handled the entire cycle—from hardware sourcing and delivery to environment configuration and turnkey setup
Anna S
Machine Learning Engineer
For processing financial analytics and contracts, a fully private RAG pipeline was critical. Querying open cloud LLMs simply wasn't an option. Quant configured a local workstation that instantly indexes our internal knowledge bases. It provides exactly the uncompromising level of data control we were looking for
David M
Senior Data Scientist
We wanted to deploy AI agents for code review and refactoring, but our security team strictly prohibited sending proprietary code to external APIs. Quant designed a dedicated Team Server for us. Now, our agents interact with repositories locally with near-zero latency, and our source code never leaves our secure perimeter.
Michael V
Lead Software Engineer
We needed a stable and independent architecture for continuous model fine-tuning on specialized tasks. The Quant team deployed a complete AI lab built around two DGX Spark machines. They handled the entire cycle—from hardware sourcing and delivery to environment configuration and turnkey setup
Anna S
Machine Learning Engineer
For processing financial analytics and contracts, a fully private RAG pipeline was critical. Querying open cloud LLMs simply wasn't an option. Quant configured a local workstation that instantly indexes our internal knowledge bases. It provides exactly the uncompromising level of data control we were looking for
David M
Senior Data Scientist
We wanted to deploy AI agents for code review and refactoring, but our security team strictly prohibited sending proprietary code to external APIs. Quant designed a dedicated Team Server for us. Now, our agents interact with repositories locally with near-zero latency, and our source code never leaves our secure perimeter.
Michael V
Lead Software Engineer
We needed a stable and independent architecture for continuous model fine-tuning on specialized tasks. The Quant team deployed a complete AI lab built around two DGX Spark machines. They handled the entire cycle—from hardware sourcing and delivery to environment configuration and turnkey setup
Anna S
Machine Learning Engineer
For processing financial analytics and contracts, a fully private RAG pipeline was critical. Querying open cloud LLMs simply wasn't an option. Quant configured a local workstation that instantly indexes our internal knowledge bases. It provides exactly the uncompromising level of data control we were looking for
David M
Senior Data Scientist
We wanted to deploy AI agents for code review and refactoring, but our security team strictly prohibited sending proprietary code to external APIs. Quant designed a dedicated Team Server for us. Now, our agents interact with repositories locally with near-zero latency, and our source code never leaves our secure perimeter.
Michael V
Lead Software Engineer
We needed a stable and independent architecture for continuous model fine-tuning on specialized tasks. The Quant team deployed a complete AI lab built around two DGX Spark machines. They handled the entire cycle—from hardware sourcing and delivery to environment configuration and turnkey setup
Anna S
Machine Learning Engineer
For processing financial analytics and contracts, a fully private RAG pipeline was critical. Querying open cloud LLMs simply wasn't an option. Quant configured a local workstation that instantly indexes our internal knowledge bases. It provides exactly the uncompromising level of data control we were looking for
David M
Senior Data Scientist
We wanted to deploy AI agents for code review and refactoring, but our security team strictly prohibited sending proprietary code to external APIs. Quant designed a dedicated Team Server for us. Now, our agents interact with repositories locally with near-zero latency, and our source code never leaves our secure perimeter.
Michael V
Lead Software Engineer
We needed a stable and independent architecture for continuous model fine-tuning on specialized tasks. The Quant team deployed a complete AI lab built around two DGX Spark machines. They handled the entire cycle—from hardware sourcing and delivery to environment configuration and turnkey setup
Anna S
Machine Learning Engineer
For processing financial analytics and contracts, a fully private RAG pipeline was critical. Querying open cloud LLMs simply wasn't an option. Quant configured a local workstation that instantly indexes our internal knowledge bases. It provides exactly the uncompromising level of data control we were looking for
David M
Senior Data Scientist
We wanted to deploy AI agents for code review and refactoring, but our security team strictly prohibited sending proprietary code to external APIs. Quant designed a dedicated Team Server for us. Now, our agents interact with repositories locally with near-zero latency, and our source code never leaves our secure perimeter.
Michael V
Lead Software Engineer
We needed a stable and independent architecture for continuous model fine-tuning on specialized tasks. The Quant team deployed a complete AI lab built around two DGX Spark machines. They handled the entire cycle—from hardware sourcing and delivery to environment configuration and turnkey setup
Anna S
Machine Learning Engineer
For processing financial analytics and contracts, a fully private RAG pipeline was critical. Querying open cloud LLMs simply wasn't an option. Quant configured a local workstation that instantly indexes our internal knowledge bases. It provides exactly the uncompromising level of data control we were looking for
David M
Senior Data Scientist
We wanted to deploy AI agents for code review and refactoring, but our security team strictly prohibited sending proprietary code to external APIs. Quant designed a dedicated Team Server for us. Now, our agents interact with repositories locally with near-zero latency, and our source code never leaves our secure perimeter.
Michael V
Lead Software Engineer
We needed a stable and independent architecture for continuous model fine-tuning on specialized tasks. The Quant team deployed a complete AI lab built around two DGX Spark machines. They handled the entire cycle—from hardware sourcing and delivery to environment configuration and turnkey setup
Anna S
Machine Learning Engineer
For processing financial analytics and contracts, a fully private RAG pipeline was critical. Querying open cloud LLMs simply wasn't an option. Quant configured a local workstation that instantly indexes our internal knowledge bases. It provides exactly the uncompromising level of data control we were looking for
David M
Senior Data Scientist
PRICING
Choose your level of help
Pay for implementation only when you want us to take responsibility
AI Machine Plan
$299
One clear use case
Primary & alternative hardware
Exact buy list
Model and agent plan
DIY setup sequence
One 30-minute review call
Advice only (no remote login)
Set Up My Machine
from
$2,500
Configure your own hardware
System preflight included
One supported model path
One agreed agent path
Secure remote access
One acceptance task
Complete handover
Source & Set Up
from + hardware
$5,000
Hardware finalisation
Purchase coordination
Receive and test equipment
Stack configuration
Delivery within the UAE
International delivery on request
Custom AI System
Tailored architectures and enterprise deployments. Priced after technical discovery
AI Machine Plan
$299
One clear use case
Primary & alternative hardware
Exact buy list
Model and agent plan
DIY setup sequence
One 30-minute review call
Advice only (no remote login)
Set Up My Machine
from
$2,500
Configure your own hardware
System preflight included
One supported model path
One agreed agent path
Secure remote access
One acceptance task
Complete handover
Source & Set Up
from + hardware
$5,000
Hardware finalisation
Purchase coordination
Receive and test equipment
Stack configuration
Delivery within the UAE
International delivery on request
Custom AI System
Tailored architectures and enterprise deployments. Priced after technical discovery
AI Machine Plan
$299
One clear use case
Primary & alternative hardware
Exact buy list
Model and agent plan
DIY setup sequence
One 30-minute review call
Advice only (no remote login)
Set Up My Machine
from
$2,500
Configure your own hardware
System preflight included
One supported model path
One agreed agent path
Secure remote access
One acceptance task
Complete handover
Source & Set Up
from + hardware
$5,000
Hardware finalisation
Purchase coordination
Receive and test equipment
Stack configuration
Delivery within the UAE
International delivery on request
Custom AI System
Tailored architectures and enterprise deployments. Priced after technical discovery
FINDER
What should you actually buy?
What should you actually buy?
Answer eight short questions. Get a starting path, the trade-offs and a rough hardware budget.
Who is this for?
FAQ
Common questions
Short answers about the Plan, setup, builds and support.
Do I need a DGX Spark?
Better than ChatGPT or Claude?
Will everything stay private?
Can you use hardware I already own?
Can you source and deliver the hardware?
What is included in the $299 Plan?
What if I cannot follow the instructions?
What counts as custom work?
Do you offer ongoing support?
Can you build security research systems?