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Intelligent Augmentation is the result of combing large language models with a technique called Retrieval Augmented Generation (RAG). We analyse documents provided by your organisation, for example clinical guidelines, SOPs, policies, phonebooks and org charts then train sophisticated models on that data.

Our goal isn't Artificial Intelligence, it's Intelligent Augmentation.

Clinical guidelines tree connected


Dr Adam Julius is an Anaesthetic Registrar, AI researcher and entrepreneur based in London. His clinical interests include clinical risk prediction in major surgery, machine learning analysis in thomboelastography and improving patient outcomes by reducing variation in care. 

He completed a clinical fellowship in Artificial Intelligence in Prof Parashkev Nachev’s Wellcome High Dimensional Neurology Lab, developing experience in natural language processing, language models and retrieval augmented generation (RAG) techniques.

Clinical guidelines roots


Dr. Salah Hammouche, with a diverse background as an orthopedic surgeon and biomedical engineer, is advancing in Clinical Artificial Intelligence through a fellowship at London AI Centre and a Topol Digital Health Fellowship at NHS Digital Academy. He holds dual board-certification from reputable orthopedic associations, and has amassed extensive surgical experience during his residency at London Postgraduate School of Surgery. 

Academically, he earned a Ph.D. in hip replacements' tribology from the University of Leeds and has collaborated with major biomedical entities like J&J and Invibio. His recent fellowship in Clinical AI and Machine Learning is a collaborative effort among prestigious London institutions, aimed at enhancing his AI expertise alongside his orthopedic residency. 

A prolific scholar, Dr. Hammouche has over 15 published articles and abstracts, with recognition like the AAOS Resident of the Month, affirming his academic and professional prowess in the intersecting fields of orthopedics and artificial intelligence.