An AI system based on NLP and machine learning has been developed to identify surgical site infections (SSIs) from hospital discharge letters. After advanced pre-processing and imbalance handling, BERT-FT achieved the best performance (F1=0.79), outperforming TF-IDF and W2V. Large language models (LLMs) showed limitations. The system could support semi-automatic SSI surveillance, with prospects for optimisation in translations, prompts, and infrastructure.