Infinity AI Cloud Hosting

Fully managed GPU hosting for LLMs, RAG, Computer Vision and Generative AI. Deploy, fine-tune and scale on NVIDIA L4/L40S/H100—without the infra headache.

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✅ Managed NVIDIA L4 • L40S • H100
✅ vLLM • TGI • Triton preloaded
✅ RAG & Fine-tune blueprints
✅ Kubernetes autoscaling & SLOs

GPUs

L4 • L40S • H100

Stacks

vLLM • TGI • Triton

Support

24/7/365

99.95% SLA (Enterprise)

Daily Snapshots + S3 Backups

Private VLAN & Firewall

OpenAI-compatible Gateway (opt.)

Built for Teams Shipping AI

Developers & Startups

Spin up chatbots, agents, and RAG backends in minutes. Scale only when you need to.

Agencies & SaaS

Offer AI features to clients with SLAs, dashboards, and multi-tenant patterns.

Enterprises

Dedicated GPU clusters, network isolation, and compliance-ready operations.

What You Can Build

Chatbots & Assistants

Open models via OpenAI-compatible APIs. Bring your prompts, we’ll handle GPUs.

Retrieval-Augmented Generation (RAG)

Milvus/pgVector templates, ingestion pipelines, rerankers, and example apps.

Fine-Tuning & Training

LoRA/QLoRA to full multi-GPU runs with Deepspeed/FSDP and S3 checkpoints.

Vision & Media

L40S pipelines for SDXL, image/video generation, and batch processing jobs.

Why Choose Infinity AI Cloud?

Pre-Configured AI Environments

PyTorch/TensorFlow, CUDA, vLLM/TGI/Triton, JupyterLab & VS Code Server.

RAG & Fine-Tune Blueprints

LangChain, Unstructured, Milvus/pgVector, TRL, LoRA/QLoRA & Axolotl.

Managed Kubernetes Scaling

GPU Operator, KServe, KEDA autoscaling, SLO dashboards & alerts.

Security & Backups

Private VLANs, firewalls, SSL/TLS, daily snapshots & S3 object backups.

Infinity AI Cloud – Plan Comparison

Compare GPUs, resources, and included software across AI plans. Use the tabs to switch views — only one is shown at a time.

Plan	GPU	CPU / RAM	Storage	Best For	Monthly	Action
AI-VPS Core (CPU)	CPU Only	8 vCPU / 32 GB	200 GB NVMe	Embeddings, RAG API, small agents	₹9,999	Start Trial
AI-VPS Edge (L4)	1× NVIDIA L4	16 vCPU / 64 GB	400 GB NVMe	Chatbots, SD-Turbo, medium RAG	₹29,999	Start Trial
AI-K8s Inference (2×L4)	2× NVIDIA L4	32 vCPU / 128 GB	800 GB NVMe	High-TPS APIs, multi-tenant SaaS	₹49,999	Start Trial
AI-K8s Vision (L40S)	1× NVIDIA L40S	48 vCPU / 192 GB	1.6 TB NVMe	Vision, video, SDXL pipelines	₹79,999	Start Trial
AI-Pro Train-2 (2×H100)	2× NVIDIA H100 (SXM)	64 vCPU / 512 GB	3.2 TB NVMe	LoRA/QLoRA fine-tuning, RLHF	₹1,49,999	Request Quote
AI-Pro Train-4 (4×H100)	4× NVIDIA H100 (SXM)	96 vCPU / 1 TB	6.4 TB NVMe	Advanced training, long context	₹2,99,999	Request Quote

Plan	GPU Details	CUDA/Driver	Network	Backups	SLA
AI-VPS Core (CPU)	—	—	1 Gbps, IPv4/IPv6 (opt.)	Daily snapshots + S3	99.9%
AI-VPS Edge (L4)	1× L4 (24GB), MIG (opt.)	CUDA 12.x / cuDNN	1–10 Gbps (DC-dependent)	Daily snapshots + S3	99.95%
AI-K8s Inference (2×L4)	2× L4 (24GB ea.), MIG (opt.)	CUDA 12.x / cuDNN	10 Gbps, Private VLAN	Namespace snapshots + S3	99.95%
AI-K8s Vision (L40S)	1× L40S (48GB), MIG (opt.)	CUDA 12.x / cuDNN	10 Gbps, Private VLAN	Namespace snapshots + S3	99.95%
AI-Pro Train-2 (2×H100)	2× H100 (80GB), NVLink	CUDA 12.x / cuDNN	25–100 Gbps (IB/NVLink)	Checkpoint to S3 + snapshots	99.95%
AI-Pro Train-4 (4×H100)	4× H100 (80GB), NVLink	CUDA 12.x / cuDNN	100–200 Gbps (IB/NVLink)	Checkpoint to S3 + snapshots	99.95%

Plan	Frameworks	Inference	Training	RAG	Observability
AI-VPS Core (CPU)	PyTorch, TensorFlow	llama.cpp / Ollama (CPU)	LoRA (CPU-friendly)	pgVector/Milvus (shared), LangChain	Prometheus, Grafana
AI-VPS Edge (L4)	PyTorch, TF, CUDA	vLLM, TGI, Triton	Deepspeed (opt.), TRL, LoRA/QLoRA	pgVector/Milvus, Redis, Unstructured	DCGM GPU, Prom/Graf
AI-K8s Inference (2×L4)	PyTorch, TF, CUDA	KServe + vLLM/Triton	Deepspeed/FSDP (opt.)	Managed pgVector/Milvus namespaces	Loki logs, SLO dashboards
AI-K8s Vision (L40S)	PyTorch, TF, CUDA	Triton / vLLM + SDXL presets	Vision/SD pipelines	MinIO buckets + rerankers	GPU, latency & TPS dashboards
AI-Pro Train-2 (2×H100)	PyTorch 2.x, CUDA	Triton (opt.)	Deepspeed, FSDP, TRL, Axolotl	S3 checkpoints, vector DB (opt.)	Prom/Graf/Alerting
AI-Pro Train-4 (4×H100)	PyTorch 2.x, CUDA	Triton (opt.)	Deepspeed, FSDP, TRL, Axolotl	S3 checkpoints, vector DB (opt.)	Prom/Graf/Alerting

Pre-Configured AI Stack

Frameworks

PyTorch 2.x, TensorFlow 2.x, Hugging Face Transformers, CUDA/cuDNN.

Inference

vLLM, Text Generation Inference (TGI), Triton, llama.cpp high-perf builds, Ollama.

Training & Fine-Tuning

Deepspeed, FSDP, TRL, LoRA/QLoRA, Axolotl, Accelerate; S3 checkpoints.

RAG Toolkit

Milvus/pgVector, Redis, LangChain, Unstructured, FastAPI reference project.

Observability

Prometheus/Grafana dashboards, DCGM GPU metrics, Loki logs, alerting/SLOs.

Storage

NVMe local + S3-compatible object storage (MinIO/AWS) with lifecycle policies.

Operations You Can Trust

Security

DDoS protection, firewalls, private VLAN/VPC, SSL/TLS, image allow-lists, signed containers.

Backups & DR

Daily snapshots + S3 backups, retention policies, point-in-time restores on request.

SLA & Support

24/7/365 monitoring, 99.95% SLA (Enterprise), priority incident response, change windows.

Add-Ons

Additional GPU nodes (hourly/monthly)
Managed Vector DB (Milvus/pgVector), Redis, PostgreSQL
OpenAI-compatible AI Gateway (central endpoint for your apps)
Private S3 buckets with lifecycle management
Partner/Reseller accounts with 25% recurring commissions

What Customers Say

“We launched our chatbot with Infinity AI Cloud in days. The GPU autoscaling and SLO dashboards saved us weeks.”
— Product Lead, SaaS Startup

“Their RAG template plus managed pgVector got our knowledge base bot live with zero infra hassles.”
— CTO, Services Agency

Frequently Asked Questions

Can I bring my own model and code?

Yes. We support vLLM/TGI/Triton and provide an OpenAI-compatible gateway so your existing code works with minimal changes.

Do you support LoRA/QLoRA fine-tuning?

Yes. Use our finetuning images with TRL/Axolotl/Deepspeed. Checkpoints save to S3 for quick resume.

How do backups work?

Daily snapshots plus S3 backups with retention. We can restore to a point-in-time snapshot on request.

Is there usage-based autoscaling?

On Kubernetes plans, KEDA reacts to queue depth/latency to scale pods. We can add GPU nodes on demand (add-on).

Can I get a dedicated private cluster?

Yes. We offer dedicated L40S/H100 or AMD MI300X clusters with private networking and custom SLAs.

What about data security?

Private VLANs/VPC, firewall rules, TLS everywhere, signed containers, and per-namespace credentials for shared services.

Launch Your AI Cloud Today

Production-ready GPU hosting with expert support—from inference to full-scale training.

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