Enterprise content management is experiencing its biggest architectural shift since the cloud migration era. For years, enterprises have stored trillions of gigabytes of critical data in Box: financial models, clinical trial protocols, M&A due diligence rooms, engineering schematics, and legal compliance playbooks. Up to this point, text-based search and retrieval-augmented generation (RAG) have successfully unlocked the vast narrative knowledge within these repositories, establishing a powerful and highly effective baseline for enterprise AI intelligence.
Traditional RAG architectures have mastered text processing, but the agentic era demands more. The next logical evolution is to extend this framework to capture the inherently multimodal, deeply spatial, and highly structured elements that exist alongside text. While text embeddings excel at indexing prose, multimodal architectures unlock a major new capability: For example, they preserve the strict row-column semantics of financial tables, interpret visual evidence like clinical data, and map the logic of multi-page flowcharts without losing their spatial layout.
To deliver next-generation capabilities that can handle the vast universe of digital content, Google Cloud and Box are integrating advanced multimodal capabilities into Box's Agentic Platform , powered by Gemini Multimodal Embeddings 2 merging Box’s industry-leading Intelligent Content Management platform with Google Cloud’s advanced AI embeddings. Preserving visual and spatial geometry : Complex document elements like multi-column tables or financial matrices rely on their spatial layout to convey meaning.
Converting these elements into a flat string of text can disassociate column headers from their corresponding data points. Multimodal embeddings allow systems to interpret the document exactly as a human does, maintaining the integrity of spatial relationships. Illuminating the visual modality : Enterprise documents are filled with visual indicators: technical charts, process flowcharts, branding assets, and product photography. Multimodal capabilities ensure that these elements are no longer invisible to search systems, allowing users to query images and text simultaneously.