LOCAL AI DEPLOYMENT / SINGAPORE
Local AI deployment.
On your hardware.
Local AI deployment for individuals and teams in Singapore. A self-hosted model and agent configured on your own hardware, with testing and a guided handover.
ACCEPTING PROJECTSStart with the work you want to do.
We provide on-premise AI deployment remotely, or on site within Singapore. Start with a discussion of your tasks, users, data and location so we can agree the setup, access arrangements and project scope.
For individuals and developers
Discuss a local assistant for drafting, coding or exploring models. We assess the chosen tools and example tasks, then agree what will be included and tested.
For small teams
Discuss who needs access, the documents or applications involved, and how the setup will be maintained. Document search, integrations and concurrent use each need their own agreed scope and validation.
What your deployment includes.
- Scope: agree the intended tasks, supported software and acceptance examples.
- Deployment: configure the selected local model and its serving software on your AI Station or compatible existing infrastructure. We work remotely, or on site within Singapore, as agreed for your project.
- Workflow configuration: set up the agreed tools and settings for your use case.
- Verification: test the agreed tasks on the delivered configuration and document its practical limits.
- Handover: provide setup documentation and a guided walkthrough. Ongoing support and later changes have a separately agreed scope.
Our TQ–32 offering uses Qwen 27B with vLLM. We agree the agent interface, supported tools and acceptance tasks for your deployment. Customisation covers serving and workflow configuration; training new model weights requires a separate dataset, scope and evaluation.
One complete solution.
TQ–32 · Workstation + AI setup
The workstation, local model and agent setup, testing, documentation and guided handover.
TQ–A128 · Agent server + agent setup
An agent server for teams with TensorQuay Agent set up for you: user accounts and roles, a sandbox per agent task and a model router to local or cloud models. Delivered within 1 week. Specifications.
TQ–192 · Proposed
Our proposed dual-GPU system for larger local models and team workloads, with 192 GB of GPU memory. Pricing, supply and the supported AI setup are confirmed per quotation. Register your interest to discuss your requirements.
Explore the TQ–32 solution and pricing or read the component specifications. Every TQ–32 includes the AI setup.
Understand what runs locally.
Supported models can run inference on the workstation after installation. Downloads, updates and optional cloud, browser or communication integrations may need internet access. We will document the data flow and network requirements for the agreed setup.
The AI assistant on this website uses a cloud AI service. It is separate from the local AI on a delivered workstation. Please use non-sensitive examples when discussing your requirements here.
Read our local AI vs cloud AI guide for a practical data-flow checklist and a way to compare the options on your own tasks.
Tell us what you would like to run.
Tell us your main task, the number of users, the applications involved and your preferred timeframe. We can start scoping your deployment now.
Local AI deployment projects are open now. Hardware lead times and the supported software are agreed for each project. Explore all our services or read our local AI guides.