Pre-configured GPU servers
NVIDIA GPU servers (A100, L40S, RTX 4090) configured with CUDA, Docker, and inference frameworks. Plug in, power on, and run AI — no GPU engineering needed.
An on-premise AI server that lets Indian businesses run LLMs, RAG systems, and AI models on their own hardware — inside their own data centre or server room. DPDP Act compliant, zero cloud dependency, and full data sovereignty. GPU servers configured, delivered, and deployed by Velozity from ₹12 Lakhs.
Banking transaction data, patient records, legal documents, and government files must stay within your network. Public AI APIs like OpenAI send data to external servers — a compliance violation waiting to happen.
You spend ₹50,000-2,00,000/month on OpenAI or Azure AI APIs. Costs scale linearly with usage. At 10,000+ queries per day, on-premise is 60-70% cheaper over 2 years.
Buying NVIDIA GPUs, configuring CUDA drivers, deploying models, and managing inference servers requires specialized expertise. Most IT teams have never done this.
NVIDIA GPU servers (A100, L40S, RTX 4090) configured with CUDA, Docker, and inference frameworks. Plug in, power on, and run AI — no GPU engineering needed.
Llama 3.1, Mistral, Phi-3, and embedding models pre-installed and tested. RAG pipeline with vector database ready to use. Custom models can be added.
Your data never leaves your premises. No internet connection required for inference. Air-gapped deployment available for defence and government clients.
OpenAI-compatible API endpoint. Your existing applications work with on-premise AI by changing one URL. No code changes needed.
GPU utilisation, model performance, query latency, and error rate dashboards. Alerts for hardware issues, model degradation, and capacity limits.
Full compliance with India's Digital Personal Data Protection Act. Audit logs, access controls, and data lineage tracking. Suitable for RBI, SEBI, and HIPAA workloads.
We assess your AI use cases, data volume, query load, and latency requirements. Recommend the right GPU configuration and model selection.
We procure, configure, and test the GPU server. Pre-load your selected AI models. Typical lead time: 2-3 weeks.
We deploy the server in your data centre or server room. Configure networking, security, and API endpoints. Train your IT team on management.
Connect your applications to the on-premise AI API. Migrate from cloud AI to on-premise. Validate performance and accuracy.
Single GPU server for small-medium AI workloads.
Multi-GPU server for large models and high throughput.
Multi-server GPU cluster for enterprise-scale AI.
| Feature | Velozity | Typical alternatives |
|---|---|---|
| Data sovereignty | Your data stays on your premises | Data goes to cloud provider |
| Recurring cost | Zero API fees after purchase | ₹50K-2L/month in API costs |
| Setup complexity | Pre-configured, plug and play | DIY GPU + CUDA + model setup |
| Model flexibility | Llama, Mistral, custom models | Locked to provider models |
| Compliance | DPDP Act, RBI, air-gapped | Shared cloud infrastructure |
| India support | On-site from Chennai team | Remote ticket-based support |
Our on-premise AI servers run LLMs and document processing AI for financial institutions and healthcare organisations across India. Zero data breaches. Average query latency: under 500ms. 99.9% uptime.
Read the case studyFor 7-13B parameter models (Llama 3.1 8B, Mistral 7B): NVIDIA RTX 4090 or L40S. For 70B+ models: NVIDIA A100 80GB. For multiple large models: multi-GPU A100 setup. We recommend based on your specific use case.
Yes. Air-gapped deployment available. All models run locally. No internet needed for inference. Updates can be applied via USB.
Yes. Our inference server exposes an OpenAI-compatible API. Your existing code that uses OpenAI API works by changing the endpoint URL. No other code changes.
Hardware comes with manufacturer warranty (3-5 years). We provide software support, model updates, and on-site maintenance for the support period included in your plan.
Yes, on Enterprise and Cluster plans. We provide fine-tuning pipelines and can assist with training on your data. Starter servers are optimised for inference.
Starter server: 400-600W. Enterprise server: 1,500-3,000W. We provide power and cooling requirements during the assessment phase.
Tell us what could work better. We'll help you find the intelligent way forward.
Call us: +91 80720 64524