Box expands Nvidia partnership, unveils AI workflow builder
The company said the new search engine could improve accuracy by 20%, cut token use by 90% and answer queries four times faster.
- On Thursday, Box expanded its Nvidia partnership at its developer conference, unveiling Box Context Retrieval to improve AI search accuracy and Box Architect for building automated workflows.
- Nvidia's Nemotron embedding system powers the new search engine, using LLMs to map concepts beyond simple keywords and enabling agents to retrieve relevant document chunks more effectively.
- The engine improves search accuracy by 20%, reduces token usage by 90%, and speeds up question-answering fourfold. "This dramatically boosts both the relevance of our search technology for agents," Box CEO Aaron Levie said.
- Enterprise Advanced customers gain access to the search engine early next year, while Box Architect begins rolling out in beta during the fourth quarter. "We're probably packing in five different technologies into one simple API," Levie told TechCrunch.
- New threat protection against bulk downloads and account takeovers arrives early next year for Enterprise Advanced and Shield customers, complementing the AI-driven tools Box announced.
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15 Articles
Box and NVIDIA Build Enterprise AI Retrieval Layer Around Company Content
Box and NVIDIA have expanded their partnership with Box Context Retrieval, an engine designed to help AI agents find relevant information across enterprise files. The companies say it supports multimodal indexing and permission-aware retrieval. This post: Box and NVIDIA Build Enterprise AI Retrieval Layer Around Company Content is first published on Compsmag.com
Box Integrates Nvidia Nemotron AI Models to Improve Enterprise Search
Box has announced a new AI-powered content retrieval system that integrates Nvidia’s Nemotron embedding models to help enterprise AI agents search and analyze documents more efficiently. Introduced at the company’s developer conference on November 5, 2026, Box Content Retrieval is designed to improve search accuracy while reducing processing time and AI-related computing costs. The feature […]
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