ZOTECT DIGITAL CAPITAL CO., LTD. · AI INFRASTRUCTURE & LLMOPS

We're LeadingLLM Infrastructure& LLMOps.

At Zotect, we provide comprehensive LLM infrastructure consulting - designed to empower your business with scalable, observable, open-weight AI systems. Our expertise ensures you have the flexibility to ship production AI on your own terms.

Talk to our engineers Explore the system

Build Your AI Data Center
Break Free from Token Limits

AI Infrastructure is the foundation for advanced AI development - inference and model training through agentic AI and developer APIs without token limits, on your GPU servers.

AI Infrastructure

Design the foundation around the real workload so facility, network, storage, GPU, and Kubernetes deliver to the model as Rack to LLM - built by people who have stood up AI Factories.

Data Center Readiness
Rack, Stack and Cabling
GPU Architecture
GPU Cluster Deployment
OS Tuning & HPC Drivers
RDMA Network Fabric
High-Performance Storage
Kubernetes and Slurm

AI Infrastructure

LLMOps & AI Platforms

Take the LLM to inference, connect it to RAG, and train and fine-tune the model at peak efficiency on your GPU cluster.

Model Serving and Inference
Deployment with LLMOps
RAG Integration
LLM with IB/RoCE Network
GPU Workload Optimization
Observability

LLMOps & AI Platforms

Enabling layerModern IT Infrastructure

Stand up public cloud, private cloud, Kubernetes, network, and firewall, then bring CI/CD to your applications in a cloud-native, open-source form so the system can scale freely across a large number of workloads on cloud and on-prem.

Explore the infrastructure foundation

01Data Centers

02Network

03Compute

04Platform

05Model

06Operation

07Support

Six services
One stack

With our experience deploying GPUs, LLM inference, and LLM training and fine-tuning for hyperscalers, we raise production performance with a Rack to LLM architecture from server vendors and data centers ready for high density. You develop inference, RAG, training, and fine-tuning on a GPU cluster you control, without third-party API limits.

01 / INFBuild AI Infrastructure
02 / TRNTraining & Fine-tuning
03 / DEPModel Deployment & Serving
04 / RAGRAG & Data Integration
05 / MONMonitoring & Optimization
06 / OPSManaged LLMOps

Explore related services

01 / INFBuild AI InfrastructureDesign from the data center to the GPU cluster as Rack to LLM - rack and stack, OS tuning, and drivers for HPC - by people who have worked with NVIDIA to build NCP clusters.

02 / TRNTraining & Fine-tuningTrain and fine-tune models on your GPU cluster so the GPUs are fully used against the real workload, without depending on someone else's API.

03 / DEPModel Deployment & ServingServe inference models over an API with batching, autoscaling, and per-tenant quotas on a GPU cluster on IB/RoCE - so you can run the service without token limits.

04 / RAGRAG & Data IntegrationConnect LLMs to your documents, knowledge bases, and internal data with citation-faithful retrieval, fitted to work inside your organization.

05 / MONMonitoring & OptimizationGPU Workload Optimization, then track latency, GPU utilization, error rate, and unit cost on one observability surface - so you know early whether every GPU is fully used.

06 / OPSManaged LLMOpsOngoing operation and support of infra, monitoring, model upgrades, and incident response within an agreed scope, so your team can focus on the use case.

The stack we know cold.

10 OF 40+ TOOLS

NVIDIA
AMD
PyTorch
Kubeflow
vLLM
SGLang
Weka
Qwen3.8
DeepSeek-R1
GLM 5.2

Our Expertise

Leadership prior experience · not Zotect company delivery figures

Our team has experience designing and deploying more than 3,000 NVIDIA GPUs across multiple data centers with over 30 MW of combined power capacity, and operating more than 5,000 VMs on petabyte-scale Ceph / DDN / Weka - from site readiness and SuperPOD/HGX GPU clusters with RDMA/InfiniBand through production model serving, training / fine-tune, and LLMOps on Kubernetes with vLLM and Ray Serve.