Fine-tuning (model adjustment)

Fine-tuning consists of continuing the training of an existing model on a targeted corpus, internal case law, customer support history, technical documentation, to improve its performance on that specific domain.

For most business uses, RAG is enough and remains simpler to maintain (knowledge is updated by re-indexing documents, without retraining). Fine-tuning keeps its value for specializing a local open-source model on a domain vocabulary or a highly constrained output format.