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Build RAG workflows with document ingestion, hybrid search, and agentic answers.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ragx" yet — see the docs or source repo.
Use ragx to ingest our product manuals, FAQs, and technical docs, build a searchable knowledge base, and answer: "What access control methods does the enterprise edition support?" Include citations.
An accurate answer grounded in the ingested documents, with relevant excerpts or source citations.
Use ragx to search the uploaded project documents for "API rate limiting" and "error retry mechanisms," then summarize the most relevant results by topic.
A cross-document summary of the most relevant search results, organized by topic for quick reference.
Use ragx to list all documents in the current knowledge base, flag duplicates or outdated content, and suggest which files should be updated, removed, or re-ingested.
A document inventory with issue flags and maintenance recommendations to keep the knowledge base clean and usable.
Index documents and retrieve relevant context for better LLM responses.
Retrieve and process docs with vector search to enrich AI responses.
Let AI securely query private local documents with persistent memory.
Index documents and retrieve knowledge via keyword and vector search over MCP.
Ingest documents and query them with natural-language semantic search.
Connect local code and docs for fast AI vector-based retrieval.