Let Agent Answer Questions Based on Your Documents
Import enterprise internal documents, manuals, and regulations into the knowledge base, and Agent can answer questions based on this content — with source citations for every conclusion.
Document Support
availableSupports PDF, Word, Excel, PPT, Markdown, HTML, CSV, and more formats. Upload files or enter URLs to import. Three document chunking strategies (fixed-length, recursive, semantic) to match different document structures. Create Markdown documents directly within the knowledge base.
Precise Retrieval
availableNot simple keyword matching. The system simultaneously retrieves from both 'semantic understanding' and 'keyword matching' dimensions, then uses ranking algorithms to find the most relevant content — semantic vector retrieval captures similar meaning with different wording, keyword retrieval ensures exact hits on proper nouns and IDs. Dual-path results are merged, ranked, and refined through a re-ranking model.
Built-in Vector Database
No need to deploy additional database services — built-in embedded vector database, zero external dependencies.
Traceable Conclusions
availableEvery answer from Agent is annotated with sources:
A structured citation panel displays the complete reference source list. Lets users verify AI's judgments rather than blindly trusting them.
Knowledge Base Management
availableComplete lifecycle management: create, edit, and delete knowledge bases. Documents are processed asynchronously after upload, with failed documents retryable. View, edit, and delete individual document chunks with in-chunk text search. Knowledge bases can be bound to specific Agents, auto-retrieving relevant content at runtime.
Dedicated knowledge base detail page with document table and chunk browser, supporting direct navigation from list to document and chunk management.