LLM Fine-Tuning & Deployment
Fine-tune open-source models on your domain data and serve them on your own infrastructure: domain accuracy without recurring per-token API costs.
The problem
Paying per-token API costs at production scale is prohibitive. Generic foundation models also lack domain-specific accuracy for regulated or specialised industries.
Our approach
We fine-tune Llama 3, Mistral, Qwen, or custom base models on your proprietary data using LoRA/QLoRA, then quantise and serve them via vLLM or TGI on your own cloud infrastructure.
How we deliver it.
Every token you send to a proprietary API is a cost and a privacy risk. We handle the full fine-tuning lifecycle: dataset curation, quality filtering, LoRA/QLoRA training, RLHF alignment, quantisation, and low-latency inference serving.
What's included