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Large Language ModelsLangChain BlogPublished: Mar 27, 2026, 07:00 JST1 min read

S&P Global's Kensho uses LangGraph to build a multi-agent framework that unifies fragmented financial data access across enterprise systems.

S&P Global's Kensho uses LangGraph to build a multi-agent framework that unifies fragmented financial data access across enterprise systems.

3 Key Points

  1. Kensho developed the Grounding framework, an agentic access layer that solves trusted financial data retrieval challenges at enterprise scale

  2. LangGraph enabled the creation of a multi-agent system capable of handling complex workflows across distributed financial data sources

  3. The solution provides a unified interface to access fragmented financial data, reducing complexity for enterprise users

  4. The framework demonstrates how AI agents can be orchestrated to improve data governance and reliability in financial services

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