Mem++ is a non-destructive memory framework for long-term organizational LLM agents. It stores documents whole with their date and author, allowing for read-time selection of relevant documents and fusion of lexical and semantic rankings. Evaluations show Mem++ outperforms baseline memory systems by 8-13 points and achieves the best overall score on the gpt-4.1-mini model.