AI agents can answer questions only when they have access to the right business context. That context often lives in files across an organization: contracts, policies, project plans, research, and more. Finding the relevant information—and making it available securely and efficiently—can take significant work.
Box Context Retrieval helps agents and applications find relevant information in content stored in Box. It combines keyword matching with semantic search to surface useful passages, grouped by source file, so applications can work with focused context instead of pulling in entire documents.
What this means for your organization:
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More relevant results: Find information even when a question uses different language from the source.
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Focused context for AI: Retrieve passages with their source files to help ground responses and reduce unnecessary content sent to downstream models.
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Content that stays current: Box maintains the index as eligible content changes, reducing the need to build and maintain separate retrieval pipelines.
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Access that respects permissions: Retrieval reflects the requester’s Box permissions, so people and applications access only the content they’re allowed to see.
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No separate retrieval pipelines: Eliminate the need to build, manage, or sync custom vector databases and retrieval infrastructure—Box automatically maintains the index directly over your content.
Developers can use Context Retrieval through an API to build applications and AI experiences over Box content. It gives agents a way to work with business context while that content remains in Box and under existing governance.
Check this out to learn more: Box Context Retrieval
What kinds of applications or workflows would you want to build with Context Retrieval?