Compute & infrastructure
Scale from single-server inference to multi-node clusters with GPU selection, resource pooling, container orchestration, and high availability.
Put DeepSeek, Qwen and GLM models into your own Shenzhen operating environment, then connect WeCom, CRM, knowledge and business workflows.
This is more than model deployment. We unite compute, platforms, data, and applications into sustainable enterprise AI infrastructure.
Scale from single-server inference to multi-node clusters with GPU selection, resource pooling, container orchestration, and high availability.
Support leading open and commercial models with quantization, fine-tuning, evaluation, acceleration, and a unified model gateway.
Connect documents, databases, and business systems to create permission-aware, fully traceable enterprise RAG.
Deliver embedded AI for service, knowledge work, R&D productivity, and operational analysis.
Not sure where to begin? Start with a decision guide, a budget estimate, a two-Spark blueprint, or a completed H200 delivery case.
Dedicated pages for regional delivery, enterprise knowledge, GPU clusters, and production acceptance.
For headquarters, R&D centers, and manufacturers in Shenzhen that need models, knowledge, logs, and access control to remain in a governed environment.
View service →02Plan a controlled LLM platform for Hong Kong organizations and Shenzhen–Hong Kong teams with explicit data, access, integration, and operational boundaries.
View service →03Bridge global technology standards and local China infrastructure with a private AI platform that is deliverable, auditable, and supportable.
View service →04Answer enterprise questions while preserving document permissions, source citations, update ownership, and audit boundaries.
View service →05Scale from single-server validation to production clusters with explicit model parallelism, network, availability, and performance boundaries.
View service →06Move from a model that runs to a service that can be monitored, recovered, upgraded, and audited—with explicit acceptance criteria.
View service →07Deploy DeepSeek-family models, enterprise knowledge, invocation logs, and access controls inside your governed environment, from desktop validation to multi-node GPU clusters.
View service →Decoupled layers prevent vendor lock-in, enable a fast start, and support smooth scaling as your business grows.
Knowledge assistants AI service R&D Copilot Analytics Business agents
Agent orchestration RAG engine Vector search Tool use Prompt management
Model registry Fine-tuning Evaluation Inference Unified gateway
GPU pools Containers Heterogeneous scheduling Monitoring High availability
Security controls are built into every layer, from infrastructure to application access, so your organization retains full data sovereignty.
Request the security checklist →Models, data, and invocation logs remain in your controlled environment
Integrate with your IAM and preserve organizational and document boundaries
Audit data, models, applications, and user activity throughout the stack
Support domestic accelerators, operating systems, databases, and middleware
Our proven method adapts to your environment. Dedicated architects and delivery specialists take you from value validation to scaled production.
Define use cases, data boundaries, and security requirements
Select models, compute, and the technical approach
Install and configure infrastructure and platforms
Connect knowledge, fine-tune, and evaluate
Integrate business systems and launch
Monitor, improve, and provide dedicated support
We support companies in Shenzhen and Hong Kong, as well as multinational firms with branches or R&D teams in Shenzhen, with bilingual discovery, on-site delivery, and long-term operations.
A two-node plan for the official DeepSeek V4 Flash (0731), sized for 20–50-person teams or departments and a 10–15 concurrent-user target.
Scale from multi-GPU servers to departmental inference services, with capacity planning and acceptance tests based on concurrency, context length, data volume, and latency.
Deliver private deployment, optimization, and high availability for clusters up to 16 NVIDIA H200 GPUs and large open models such as GLM-5.2.
Subject to confidentiality, we can explain completed and accepted delivery experience by industry, scale, and architecture.
See how we handle offline environments, multi-node inference, unified APIs, and functional verification—alongside an executable desktop deployment blueprint.
A two-node enterprise GPU cluster in Shenzhen with GLM-5.2-FP8, Ray, vLLM, a unified API, and offline delivery.
A two-node local model blueprint for digital employees, operational queries, store tasks, and governed business tools.
Clear answers on models, GPU memory, in-domain data, cost, delivery, acceptance, and ongoing operations.
Separate infrastructure, software, delivery, and operations using real workload assumptions and an itemized RFQ.
Compare data boundaries, time to start, total cost, customization, performance, availability, and operations—then plan a hybrid route.
It depends on model size, precision, context length, concurrency, and latency targets. We size the workload first, then select the right platform from DGX Spark and multi-GPU servers to H200 clusters.
Models, knowledge bases, vector data, invocation logs, and access controls can remain in your data center or private cloud, with network isolation, audit, backup, and acceptance testing.
Yes. We integrate through APIs, agent tools, and inherited permissions, with clear interface specifications, data boundaries, and acceptance criteria.
Tell us about your objectives, data scale, and current environment. We will map a tailored technical route and clear delivery boundaries.
