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Gemini Embedding: Powering RAG and context engineering
Explore how organizations leverage Gemini Embedding for context-aware AI systems improving performance, accuracy, and efficiency across diverse industries.
Beyond this performance boost, our model's built-in multilingual support is a promising advancement for their global users, enabling Box AI to unlock insights from content across different languages and regions. Everlaw, a platform providing verifiable RAG to help legal professionals analyze large volumes of discovery documents, requires precise semantic matching across millions of specialized texts. Through internal benchmarks, Everlaw found gemini-embedding-001 to be the best, achieving 87% accuracy in surfacing relevant answers from 1.4 million documents filled with industry-specific and complex legal terms, surpassing Voyage (84%) and OpenAI (73%) models.
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