Intelligent AI Solutions for Modern Enterprises

We specialize in on-premise deployments where your data never leaves your infrastructure. Using vLLM and open-source models, we deploy AI entirely within your network — no external API calls, no cloud dependencies. For organizations with strict compliance requirements, we offer air-gapped deployments with no internet connectivity.

We support all major open-source LLMs including Llama 3.1/3.2, Qwen 2.5, Mistral, DeepSeek, and more. Our vLLM infrastructure can run any Hugging Face compatible model. We help you select the best model based on your use case, language requirements (including Bahasa Malaysia and Chinese), and hardware constraints.

Requirements depend on model size and throughput needs. For small deployments, a single NVIDIA RTX 4090 can run 7B-13B models effectively. For enterprise workloads, we typically recommend A100 or H100 GPUs. We can also help you set up efficient CPU-based inference for lower-volume use cases.

A basic EzyChat deployment can be completed in 1-2 weeks. Custom agentic AI development typically takes 4-8 weeks depending on complexity. Full private LLM infrastructure with RAG systems usually requires 6-12 weeks including data preparation, model fine-tuning, and integration testing.

We offer flexible support packages including system monitoring, model updates, performance optimization, and troubleshooting. For production systems, we recommend our managed service tier which includes 24/7 monitoring, automatic scaling, and priority support with guaranteed response times.

Unlike cloud AI services with per-token pricing, our on-premise solutions have predictable costs. You pay for initial deployment and optional ongoing support. There are no API fees or usage-based charges — once deployed, the infrastructure is yours to use without limits.