Private Large Language Models Fine-Tuned on Your Business Data

Supervised fine-tuning (SFT) and RLHF/DPO alignment on proprietary business datasets

Quantized 4-bit / 8-bit inference via vLLM — 5× lower GPU hosting cost

Private cloud deployment on AWS, GCP, Azure or on-premise GPU clusters

Semantic caching layer reducing redundant GPU token generation by up to 40%

RAG pipelines with hybrid dense-sparse vector retrieval for zero-hallucination answers