Workflow
AI powered search
icon
Search documents
The State of AI Powered Search and Retrieval โ€” Frank Liu, MongoDB (prev Voyage AI)
AI Engineerยท 2025-06-27 09:57
Voyage AI & MongoDB Partnership - Voyage AI was acquired by MongoDB approximately 3-4 months ago [1] - The partnership aims to create a single data platform for embedding, re-ranking, query augmentation, and query decomposition [29][30][31] AI-Powered Search & Retrieval - AI-powered search finds related concepts beyond identical wording and understands user intent [7][8][9] - Embedding quality is a core component, with 95-99% of systems using embeddings [12] - Real-world applications include chatting with codebases, where evaluation is crucial to determine the best embedding model and LLM for the specific application [14][15] - Structured data, beyond embeddings, is often necessary for building powerful search and retrieval systems, such as filtering by state or document type in legal documents [16][17][18] - Agentic retrieval involves feedback loops where the AI search system is no longer just input-output, but can expand or decompose queries [19][20] Future Trends - The future of AI-powered search is multimodal, involving understanding images, text, and audio together [23][24][25] - Instruction tuning will allow steering vectors based on instructions, enabling more specific document retrieval [27][28]