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LangGraph vs RAG vs Deep Agents: Building Financial Research AI Systems

Technical architecture diagram of a multi-agent financial research AI system. The central title text reads, 'LANGGRAPH VS RAG VS DEEP AGENTS: BUILDING FINANCIAL RESEARCH AI SYSTEMS.' The diagram shows an 'Agent Coordination Layer' including Orchestrator, Research, and Editor agents, and a 'Data & Retrieval Layer' including RAG and Live Data components, set against financial candlestick charts.

LangGraph gives you structure; RAG gives you truth; Deep Agents give you autonomy. We compare a standard LangGraph workflow against an advanced ‘Deep RAG’ architecture to see which performs better for complex financial research tasks.

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