Loading service details…
Loading service details…
We fine-tune open-weight models on customer-approved data using parameter-efficient methods such as LoRA and QLoRA, then measure the improvement against the base model before anything is deployed.
Fine-tuning changes how a model behaves: the format it writes in, the terminology it uses, how reliably it performs a narrow task. Where the requirement is access to changing documents, retrieval is usually the better tool — and we will say so. When fine-tuning is right, we run it as a measured experiment with clear acceptance criteria.
Tell us where you want to go. We’ll work through the possibilities, the practicalities and the right place to start.
Start a conversation