Agentic GraphRAG for Capital Markets

This article demonstrates how to build an Agentic GraphRAG solution for capital markets analysis using AWS services and TigerGraph.

• Combines knowledge graphs with document retrieval to answer complex financial relationship questions
• Transforms multi-day manual analysis into seconds of autonomous insight across disconnected data sources
• Uses AI agents to dynamically orchestrate queries across structured graph data and unstructured SEC filings
• Implements four custom tools: schema retrieval, graph description, GSQL queries, and 10-K document search
• Enables business users to ask natural language questions without learning specialized graph query languages
• Detects multi-hop dependencies, counterparty exposures, and supply chain risks invisible in traditional databases
• Built on Amazon Bedrock AgentCore, Strands framework, and TigerGraph with S&P 100 company data

Agentic GraphRAG enables capital markets firms to rapidly surface hidden relationship networks and risk exposures by seamlessly combining structured entity connections with contextual documentary evidence through natural language queries.