Enables semantic search of project documentation using hybrid vector and full-text search with fast and deep query modes for immediate results or complex multi-round synthesis.
Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.
Crawls documentation websites and provides semantic search capabilities over the content through vector embeddings, enabling natural language queries of technical documentation.
Transform your non-existent or unreadable docs into an intelligent, searchable knowledge base that actually answers those 'basic questions' before they're asked.
Enables AI assistants to parse and search documents including PDF, Word, Excel, PowerPoint, and images via OCR, with support for semantic search and batch processing.
Provides comprehensive access to MoEngage documentation from developers, help, and partners portals with full-text search, automatic updates, and intelligent filtering by platform, category, and source.
