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.

Built for Every Stage of the AI Lifecycle.

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

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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
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
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The Fastest Path to
Blackwell Compute.

Deploy a B200 in 60 seconds. Scale to a Grace Blackwell bare-metal cluster when you're ready. No sales calls required.