Embed is a leading multimodal search and retrieval tool. It aims to activate your enterprise data with secure AI retrieval, turning text and images into embeddings to enable semantic retrieval in search systems, RAG architectures, and agentic applications.

Key Features:

• Generates single embeddings for mixed-modality documents
• Retrieves content in 100+ languages
• Maps visual assets and written content into the same embedding space
• Handles high-context business content with precision
• Privately deployable in virtual private cloud or on-premises
• Compresses embeddings by up to 96% without sacrificing quality

Use Cases:

• Fetching relevant content for Q&A
• Surfacing task-critical context for agents
• Powering AI agents that understand business needs
• Enhancing search systems with semantic retrieval
• Integrating with RAG and agentic pipelines

Benefits:

• Improves retrieval accuracy across noisy, multilingual, and multimodal data
• Reduces vector database storage costs
• Delivers accurate results even on fragmented or domain-specific data
• Ensures data security with private deployment options
• Supports reasoning, tool use, and generation across enterprise domains