NVIDIA NeMo™ Retriever is a collection of microservices designed for building multimodal extraction, reranking, and embedding pipelines with high accuracy and maximum data privacy. It delivers quick, context-aware responses for AI applications like advanced retrieval-augmented generation (RAG) and agentic AI workflows. NeMo Retriever allows developers to flexibly leverage these microservices to connect AI applications to large enterprise datasets wherever they reside and fine-tune them to align with specific use cases.

Features

• Multimodal Extraction: Provides 15x faster multimodal PDF extraction compared to open-source alternatives.
• High Accuracy: Reduces incorrect answers by 50% when compared to open-source alternatives.
• Embedding: Boosts text question-and-answer retrieval performance with high-quality embeddings.
• Reranking: Enhances retrieval performance with a fine-tuned reranking model.
• Scalability: Supports reliable, multilingual, and cross-lingual retrieval, optimizing storage, performance, and adaptability for data platforms.

Benefits

• Efficiency: Rapidly ingests massive volumes of data and extracts text, graphs, charts, and tables simultaneously for highly accurate retrieval.
• Performance: Accelerates multimodal document extraction and real-time retrieval with lower RAG costs and higher accuracy.
• Flexibility: Allows developers to build optimized ingestion and retrieval pipelines for highly accurate information retrieval at scale.
• Integration: Works seamlessly with other NVIDIA NeMo microservices for comprehensive AI workflows.