AI LLM Ops Services
Design, Install, and Manage Large Language Model Systems for Enterprises
Production-Ready, Secure, Scalable, and Cost-Controllable
LLMOps is about moving LLM usage in organizations beyond experimentation — enabling systematic real-world deployment covering infrastructure, model serving, internal data integration, RAG, and full Monitoring, Security, and Governance management.

Ref. https://developer.nvidia.com/embedded/develop/software
Our Expertise
- ประสบการณ์กับ Large-Scale Models We have hands-on experience designing and running large-scale models such as DeepSeek 671B, Llama 3.1 405B, and OSS GPT 120B for real enterprise-grade workloads.
- Expertise in Model Serving Stack We have deployed and operated Model Serving systems using KServe, vLLM, Ray Serve, and Kubeflow to enable flexible and scalable inference.
- RAG on Enterprise GPU Infrastructure We have experience deploying RAG systems on high-end GPU Infrastructure such as NVIDIA H100, H200, B200, and MI300 to support high-performance AI workloads.
- AI Storage & Data Architecture We design and manage High Performance Storage tailored for AI Workloads including Inference, RAG, and Training, and help architect efficient S3-based data structures.
- Training & AI Platform Deployment We can advise, design, and deploy Model Training systems on GPU Servers, including helping plan Data Pipeline management and Environment setup for production-ready use.
Our Services
- LLM Infrastructure Design
We architect infrastructure for LLM deployments across On-Premise, Cloud, and Hybrid environments, tailored to your workload scale, budget, and organizational goals. - Model Deployment & Serving
We install and fine-tune systems for deploying models and serving them via API, enabling internal teams or applications to call them efficiently. - RAG & Data Integration
We connect LLMs to documents, knowledge bases, or internal organizational data, enabling the model to answer questions accurately with references to real business data. - Monitoring & Optimization
We set up monitoring systems for model and infrastructure performance metrics such as Latency, GPU Utilization, Error Rate, and cost, enabling easier management and optimization. - Security & Governance
We design security measures including access control, log management, and data usage guidelines to support enterprise-grade deployments. - Managed LLMOps Services
We provide end-to-end LLM system management covering infrastructure maintenance, system monitoring, updates, troubleshooting, and continuous improvement.
Technologies & Environments We Support
- Large Language Models Supporting both Open-Source and Enterprise Models for Inference, Fine-Tuning, and Enterprise AI Use Cases.
- Serving Platforms Supporting KServe, vLLM, Ray Serve, Kubeflow, and Kubernetes-based AI Platforms.
- GPU Infrastructure Supporting design and operation on GPU Servers and GPU Clusters such as NVIDIA H100, H200, B200, and AMD MI300.
- Storage & Data Layer Supporting data infrastructure setup on S3, High Performance Storage, and Data Architecture suited for AI Pipelines.
Ideal For
- Organizations Wanting to Use LLM Internally
Suitable for teams looking to build AI Assistants, Chatbots, or internal document search systems. - Businesses Moving from PoC to Production
We help transition from experimental systems to stable, real-world deployments that support users long-term. - Organizations That Need Full Control Over Data and Systems
Suited for high-privacy workloads requiring deployment on Private Environments, On-Premise, or Hybrid Architecture. - Teams Needing Training and Serving on the Same Platform
Ideal for organizations needing end-to-end AI data management including Inference, RAG, and Fine-Tuning on a unified platform.
What You Will Get
- Production-Ready AI Platform A production-ready system architecture supporting Model Serving, RAG, Training, and internal organizational data integration.
- Better Performance & Cost Control You get a system designed specifically for AI Workloads, improving performance and better controlling infrastructure costs.
- Secure & Scalable Foundation You get a system that is secure, standards-compliant, and scalable to grow with your business.
Why Choose Us
- Real Experience with Models and Infrastructure We go beyond theoretical understanding — we have direct, hands-on experience running and serving large-scale models on real GPU Infrastructure.
- Understanding Models, Platforms, and Storage We oversee the entire system — from Model Serving, RAG, Training, Storage, Kubernetes, to Data Architecture — ensuring they work seamlessly together.
- Built for Real Enterprise Workloads Every design is focused on real Production use — not just a Demo or Prototype.
Get Started with Us
If you are looking for a team to help set up an LLM system that is truly production-ready for your organization
We are ready to help you design, install, and manage a complete system — from Model Serving, RAG, Training, all the way to an AI Data Platform.
Turn LLM from a concept into a working real-world system.
Interested? Contact us by Email [email protected]
AI Chat Bots
Used to answer questions from internal documents, manuals, or company knowledge bases — helping reduce team workload and speed up information access.
Model Serving
Supporting the integration of LLM into business systems or applications such as AI Assistants, Customer Support, or data analytics systems.
RAG
Helps users search and summarize information from files, documents, or internal organizational data — accurately and quickly.
PRIVATE LLM
Ideal for organizations that need to run models within their own systems — for better control over data, security, and access.
