Nave Algarici

Nave Algarici is an AI and deep learning product manager at NVIDIA, responsible for NeMo Retrieval and a member of the NeMo-LLM product team. Before joining NVIDIA, Nave managed the AI research and development at Voca, acquired by Snap. He holds an MBA from UC Berkeley Haas School of Business and master’s and bachelor’s degrees in Electrical Engineering from Ben Gurion University, Israel.
Nave Algarici NVIDIA

Posts by Nave Algarici

Agentic AI / Generative AI Feb 04, 2026

How to Build a Document Processing Pipeline for RAG with Nemotron 

What if your AI agent could instantly parse complex PDFs, extract nested tables, and "see" data within charts as easily as reading a text file? With NVIDIA... 9 MIN READ
Agentic AI / Generative AI Mar 18, 2025

NVIDIA NeMo Retriever Delivers Accurate Multimodal PDF Data Extraction 15x Faster

Enterprises are generating and storing more multimodal data than ever before, yet traditional retrieval systems remain largely text-focused. While they can... 11 MIN READ
Agentic AI / Generative AI Mar 06, 2025

How Using a Reranking Microservice Can Improve Accuracy and Costs of Information Retrieval

Applications requiring high-performance information retrieval span a wide range of domains, including search engines, knowledge management systems, AI agents,... 8 MIN READ
Agentic AI / Generative AI Dec 17, 2024

Develop Multilingual and Cross-Lingual Information Retrieval Systems with Efficient Data Storage

Efficient text retrieval is critical for a broad range of information retrieval applications such as search, question answering, semantic textual similarity,... 8 MIN READ
An illustration representing text retrieval pipelines for RAG.
Agentic AI / Generative AI Jul 23, 2024

Develop Production-Grade Text Retrieval Pipelines for RAG with NVIDIA NeMo Retriever 

Enterprises are sitting on a goldmine of data waiting to be used to improve efficiency, save money, and ultimately enable higher productivity. With generative... 6 MIN READ
Illustration demonstrating RAG.
Agentic AI / Generative AI Feb 23, 2024

Evaluating Retriever for Enterprise-Grade RAG

The conversation about designing and evaluating Retrieval-Augmented Generation (RAG) systems is a long, multi-faceted discussion. Even when we look at retrieval... 14 MIN READ