Instant Search Brings AI To Local Files

Instant Search targets a real weakness in desktop search: knowing what a document contains but not what it is called. Its local-first approach is compelling, though the 95% accuracy claim needs independent validation.

• –Semantic retrieval can surface files based on descriptions, concepts, and page-level content
• –On-device indexing improves privacy and avoids sending sensitive documents to cloud services
• –Embedding-based search may be especially useful for large research, project, and documentation folders
• –Local indexing introduces tradeoffs around storage, compute usage, and keeping results synchronized
• –The product competes with Spotlight and emerging AI file-search tools by emphasizing precision rather than general-purpose assistance