Grounded Intelligence for Enterprise AI
RAG ensures AI reasoning and automation are driven by verified enterprise knowledge, not assumptions.
Grounded Responses
Deliver answers and outputs sourced from trusted enterprise knowledge.
Context-Aware Reasoning
Provide AI agents and assistants with relevant, real-time enterprise context.
Governed Retrieval and Generation
Apply permissions, audit trails, and controls to every retrieval and response.
What Is RAG?
Retrieval-Augmented Generation connects AI reasoning to enterprise knowledge at the moment of execution. Instead of relying on static model memory, Cuva retrieves relevant context from knowledge bases, knowledge graphs, and connected systems, then uses that context to generate accurate, explainable outputs.
RAG operates as a core capability within Cuva's knowledge systems and is governed by the operating fabric.
Core Capabilities
RAG delivers enterprise-grade intelligence through these foundational capabilities.
Source-Aware Retrieval
Retrieve relevant information from structured and unstructured enterprise sources with full source attribution.
Knowledge Graph Assisted Context
Use entity relationships to enrich retrieval and improve relevance and precision.
Permission-Aware Access
Ensure retrieval and responses respect enterprise access controls and data policies.
Traceable Responses
Provide citations, references, and execution logs for every response and action.
How It Works
RAG operates in four seamless stages to deliver grounded, actionable intelligence.
Index and Structure
Enterprise data and documents are ingested, structured, and continuously updated by agentic ETL into knowledge systems.
Retrieve Relevant Context
When a query or workflow step runs, RAG retrieves the most relevant context using semantic and structured signals.
Ground and Reason
AI models reason over retrieved context, applying financial logic and policies to generate accurate outputs.
Respond or Act
Results are returned to users through assistants or used by agents to trigger actions and workflows.
Where RAG Is Used
RAG powers intelligent capabilities across the Cuva platform.
Why It Matters
RAG reduces hallucinations, improves decision quality, and enables safe use of AI in regulated financial environments. By grounding AI behavior in enterprise knowledge, teams gain trust, accuracy, and accountability.
Relationship to Other Platform Components
RAG ensures intelligence across the platform is contextual and trustworthy.
Knowledge Systems
Provide retrieval and structure
Knowledge Assistant & CuvaBot
Consume grounded responses
AI Agents & Workflows
Act on retrieved context
Operating Fabric
Enforces governance, security, and audit controls
Ready to Experience Grounded AI?
See how RAG powers intelligent, trustworthy automation across your financial enterprise.