DenserRetriever is an AI retrieval framework purposely created to support RAG setups. It capitalizes on the strength of widespread community collaboration, being a completely open source initiative. The tool integrates with xgboost, utilizing machine learning practices to merge heterogeneous retrievers. Being Enterprise-ready means it is optimally structured to meet the demands of even the most significant organizations, indicating its scalability in diverse conditions. Running DenserRetriever is effortlessly executed, with phrases such as 'Docker Compose Up' making instantiation a breeze. Performance-wise, the tool has proven to be highly effective, accomplishing top-tier accuracy in MTEB Retrieval benchmarking. DenserRetriever is to be self-hosted, coming with a particularly simplistic docker configuration. As being an open source software, this tool is available free of charge and is adaptable for commercial uses. Users are encouraged to report issues or suggest features for enhancement where necessary. The tool is under continual development, with the Beta version of DenserRetriever V1 forthcoming.