---
title: "TrndX SDC | AI Compute"
description: "Get dedicated GPU infrastructure with bare-metal or fully managed AI Cloud options. Build, train and deploy AI workloads with TrndX SDC."
url: "https://sdc.trndx.ai/"
canonical: "https://sdc.trndx.ai/"
provider: "TrndX SDC"
type: "website"
generated: "2026-10-26"
---

# TrndX SDC | AI Compute

> Get dedicated GPU infrastructure with bare-metal or fully managed AI Cloud options. Build, train and deploy AI workloads with TrndX SDC.

Canonical page: https://sdc.trndx.ai/

---

**TrndX SDC** (**Specialized Data Center**) — an open platform without public-cloud restrictions, built for engineers, DevOps and AI engineers. Come experiment with us and experience production quality with complete freedom.

Available now  Tier-IV Partnered data center

## Next-generation AI infrastructure. Reclaim control of your resources.

TrndX SDC gives your team accelerated compute of its own.  
Take it as bare metal and run your own stack, or with AI Cloud orchestrating the whole deployment for you.

[Read Blog](https://www.trndx.ai/blogs/ai-sdc-the-spectrum-of-control/)

Option 1

Self-managed

#### Bare metal GPUs

We bring the infra. You bring the stack.

Option 2

Fully managed

#### [AI Cloud](#ai-cloud)

We run the stack for you

[Sign Up Now](#contact)

Services & configurations

### Find the precise AI infrastructure to power your workloads.

Start from a configuration that already works, or from your workload.

Start from a configuration

#### Ready-to-deploy options\

Proven NVIDIA H100 SXM configurations for workloads you already understand.

| Configuration | vCPU | System RAM | Local NVMe |
| --- | --- | --- | --- |
| 1 GPU | 16 | 256 GB | 750 GB |
| 2 GPUs | 32 | 512 GB | 1.5 TB |
| 4 GPUs | 64 | 1 TB | 3 TB |
| 8 GPUs | 128 | 2 TB | 6 TB |

\*Additional CPU compute, memory and storage available on request. Every deployment follows the same three steps.

Start from your workload

#### Tell us what you're running

For workloads that are large, unusual, or still taking shape. Our engineers size and design the deployment with you.

From first call to production

-   1
    
    **Assess** A deployment designed around your workload, not a fixed catalog.
    
-   2
    
    **Proof of conceptNo cost** One week of unlimited GPU usage on your real workloads.
    
-   3
    
    **Go live** Managed deployment with zero disruption.
    

Add managed services

#### Extend either option with specialized managed services

Reduce operational burden, improve performance efficiency, and scale as your business grows.

**Advanced observability**

**AI workload performance**

**Managed security operations**

**Backup & disaster recovery**

**Technical advisory**

AI Cloud

### One future-ready console for your entire deployment.

AI/ML Workbench & Kubeflow Capabilities included:

#### Unified platform

-   Notebooks
-   Model serving
-   Tuning & training
-   Observability & monitoring
-   Cluster management

#### Full lifecycle coverage

-   Data preparation
-   Model registry
-   Central dashboard
-   Model inference
-   AI applications

#### Pipelines & composable components

-   Integrated pipelines for orchestration
-   Workflows
-   Schedules
-   Artifact storage
-   Recurring pipeline runs

Who we serve

### Built for where you are now.

We meet every team where they are — from a first notebook to a fleet you configure yourself, on the same dedicated GPUs.

#### Application teams

Launch a notebook or inference endpoint in minutes, with no underlying infrastructure to manage.

#### ML engineers

Run on dedicated hardware with your own stack, on a platform that stays out of your way.

#### Educators

Give every student a managed environment, while advanced learners build and configure clusters hands-on.

#### Growing teams

Move between levels as your workload evolves, without changing platforms.

Contact us

### Tell us what you need.

What happens next

We reply within one working day and set up a 30-minute call on your requirement. If it’s a fit, we open a proof of concept on live capacity.