Case Study: Madrigal Pharmaceuticals builds a scalable multi-agent research platform with LangChain and LangSmith

Madrigal Pharmaceuticals deploys enterprise multi-agent research in weeks with LangChain

Madrigal Pharmaceuticals faced the challenge of integrating, searching, and synthesizing information from numerous disconnected internal and external datasets. To build a scalable and trusted multi-agent research platform, they partnered with vendor LangChain, utilizing the LangChain framework and the LangSmith platform.

The LangChain solution provided a multi-agent system where data sources were abstracted into a consistent tool interface and workflows were built as modular skills. This was deployed and monitored using LangSmith, which offered full observability and managed CI/CD. The result was a highly flexible platform that reduced the development time for new use cases from weeks to hours. Madrigal was able to move from prototype to enterprise-wide deployment in just weeks, dramatically accelerating their research to impact patients.

Madrigal Pharmaceuticals