Inference servers for production LLM workloads
IFT helps match GPU server capacity, memory, storage, networking, power, and cooling to LLM inference requirements such as concurrency, latency, throughput, and operating cost.
LLM Inference Server
LLM Inference Server Solutions for Private AI
IFT supports LLM inference server planning and deployment for organizations that need local model serving, private AI workloads, AI agents, and scalable token-generation capacity.
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Private deployment for enterprise control
LLM inference servers can support internal chat, RAG, knowledge-base Q&A, AI agents, document processing, and business workflow automation without relying only on public cloud APIs.
Scalable path from server to cluster
IFT supports deployment from single inference servers to multi-node GPU clusters with rack integration, system setup, testing, and operations support.
Capabilities
Built for procurement, deployment, and operations.
LLM inference workload assessment
GPU server configuration planning
Private model-serving infrastructure
Rack and network integration
System setup and acceptance testing
Scale-out planning for future demand
Private LLM serving
Enterprise chatbot infrastructure
RAG and knowledge-base workloads
AI agent runtime infrastructure
High-throughput token generation
What is an LLM inference server?
An LLM inference server is a compute system, usually GPU-accelerated, used to run trained large language models for production responses, private model serving, AI agents, or RAG workloads.
Does IFT support private LLM deployment?
Yes. IFT supports private LLM inference server deployment, including GPU server selection, rack deployment, system setup, testing, and operations support.
Plan your AI infrastructure deployment with IFT.
Share your workload, server quantity, GPU requirements, site conditions, target region, and timeline. IFT will help evaluate the right deployment path.
Contact IFT