AI Inference & Deployment

Serve Models at Lightning Speed.

Deploy high-throughput inference endpoints powered by NVIDIA H200 GPUs. Deliver real-time predictions for LLMs, vision, and multimodal applications — all while reducing latency and optimizing GPU utilization.

Deploy Inference View Pricing

// Solution Overview

Built for Every Stage of the AI Lifecycle.

Purpose-built infrastructure aligned to your workflow — from experimentation through production deployment at scale.

⚡

Sub-5ms p99 inference, production-ready

Optimized for TensorRT, Triton, and ONNX Runtime with auto-scaling infrastructure for dynamic workloads. Optional managed Kubernetes for full MLOps integration.

Ideal For

Chatbots, copilots, and generative assistants
Model inference for NLP, CV, and speech
Edge and production inference pipelines

Highlights

Optimized runtimes: TensorRT, Triton, ONNX Runtime, vLLM
Auto-scaling endpoints — scale to zero idle, burst in <60s
Optional managed Kubernetes for MLOps integration
Real-time observability via Prometheus + Grafana

Deploy Inference

neocloudz — inference-deploy

$ neocloudz deploy --model llama-3.1-70b --gpu h200 --replicas 4[INFO] Pulling model weights from registry...[INFO] Building TensorRT engine for H200...[OK] Engine compiled in 47s — FP8 quantization enabled[INFO] Provisioning 4x H200 inference replicas...[INFO] Configuring autoscaler (min: 1, max: 16)[OK] Endpoint live: https://api.neocloudz.io/v1/llama-70b$ curl -X POST $ENDPOINT --data '{"prompt": "Hello"}'[METRICS] p50: 2.1ms | p99: 4.6ms | RPS: 1,840[METRICS] GPU Util: 92% | Tokens/sec: 18,400

Serve Models at Lightning Speed.

Built for Every Stage of the AI Lifecycle.

Sub-5ms p99 inference, production-ready

One platform. Every workload.

Your AI Infrastructure Starts Here.