Inference servers for production workloads
IFT maps inference server configuration to concurrency, latency, throughput, GPU memory, storage, network, power, cooling, and reliability requirements.
Inference Server
Inference Server Solutions for AI Model Serving
IFT provides inference server planning and deployment for enterprises running LLMs, model serving, AI agents, RAG systems, multimodal workloads, and private AI applications.
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Private model serving infrastructure
Inference servers can support enterprise chat, RAG, AI agents, knowledge-base Q&A, document processing, and internal business workflow automation.
Deployment support beyond configuration
IFT supports server delivery, rack integration, base environment setup, management readiness, acceptance testing, troubleshooting, and scale-out planning.
Capabilities
Built for procurement, deployment, and operations.
Inference workload assessment
GPU and CPU inference server planning
Model-serving infrastructure deployment
Rack and network integration
System setup and acceptance testing
Operations and expansion support
LLM inference
Model serving
RAG applications
AI agent workloads
Private enterprise AI deployment
What is an inference server?
An inference server is a compute system used to run trained AI models in production, serving responses for applications such as LLMs, RAG, AI agents, and multimodal workloads.
Can inference servers use GPUs?
Yes. Many inference servers use GPUs to improve throughput, latency, and model-serving capacity, especially for LLM and multimodal workloads.
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