The system uses large language models to compile notes, decisions, and reports into a coherent knowledge graph, then generates tailored views for different stakeholders. It was first deployed on its own development project, demonstrating that this approach can answer questions more accurately and efficiently than passing raw context to an LLM, while gap-detection and a 2-layer permission model help prioritise missing knowledge and protect confidential information.