Agentic RAG.
Beyond Static Retrieval.
Traditional RAG is linear. Agentic RAG introduces autonomous decision-making at every stage with MCP + A2A protocol integration.
Intelligent Indexing
Agents autonomously decide what to index via MCP-enabled tool integration.
Dynamic Retrieval
Retriever routers select the optimal data source for each query.
Multi-Agent Reasoning
Specialized agents coordinate via A2A protocol for parallel analysis.
Verified Generation
Critic agents validate outputs through iterative refinement loops.
Human Validation
Expert review before delivery. Zero hallucination guarantee.
MCP + A2A Native
Built on Anthropic's Model Context Protocol and Google's Agent2Agent standard.
Context Management
MCP eliminates 1,200+ daily context switches for developers
Tool Standardization
Universal interface for LLMs to interact with external systems
Agent Interoperability
A2A enables cross-platform agent communication
Enterprise Security
Built on OpenAPI authentication with audit logging
Continuous Learning Loop
Our agents don't just execute—they learn. Every interaction feeds back into the knowledge base, improving retrieval accuracy over time.