What this model category solves
RAG Models connect LLM reasoning with your trusted documents, policies, and operational data. They improve factuality, support citations, and enable safer decision support where source fidelity is critical.
Texts Models
Retrieval Augmented Generation (RAG) Models
Knowledge-grounded text models that combine retrieval pipelines with generation to reduce hallucinations and improve traceability.
Retrieval Augmented Generation (RAG) Models — Interactive Build
Tap any part or tool to detach it
Drag to move · tap again to snap it back · drag the empty background to glide the whole assistant · double-click the background to reset
Core capabilities
- Context injection from enterprise knowledge bases and documents
- Citation-aware responses with source-grounded answer generation
- Pluggable retrieval strategies across vector, keyword, and hybrid search
Best-fit use cases
- Knowledge assistants for SOPs, compliance, and policy lookup
- Customer support answers grounded in product documentation
- Expert copilots that reason over domain-specific internal corpora
Ground every answer in trusted enterprise knowledge
SetuMind AI can architect retrieval pipelines, indexing strategy, and quality evaluation loops for high-confidence responses.
Bridging AI Agents, Robots, 🚀... Amplifying Intelligence.
Building the future of connected artificial intelligence