The collaboration will allow LSEG customers to connect with the company’s licensed data to build AI agents in Microsoft Copilot Studio, the companies said in a Monday (Oct. 13) press release.
It also enables LSEG customers to use the Model Context Protocol (MCP) open-source standard for enhanced connectivity and interoperability with their own AI systems and other third-party applications, according to the release.
LSEG’s AI Ready Content and taxonomies include datasets stretching back over decades, per the release.
“LSEG’s partnership with Microsoft is transforming access to data for financial professionals with cutting-edge, AI-driven innovation at scale,” LSEG Group CEO David Schwimmer said in the release. “LSEG customers can build, deploy and scale agentic AI directly into their workflows with secure, seamless connectivity through MCP.”
Microsoft’s Copilot Studio is a low-code platform that helps users create, customize and deploy AI agents that can be integrated into workflows through Microsoft 365 Copilot and other applications, for secure and compliant customization at scale, according to the release.
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“By combining LSEG’s trusted market data with Microsoft’s cloud and AI capabilities, we’re empowering customers to unlock deeper insights, accelerate decision-making and streamline complex workflows,” Nick Parker, chief business officer and president, worldwide sales and solutions, at Microsoft, said in the release.
In another partnership involving AI, LSEG and Databricks said Sept. 23 that they teamed up to bring AI-ready financial data to Databricks customers, enabling them to build and deploy AI agents on their own enterprise data and LSEG’s data. With these resources and Databricks Agent Bricks, Databricks customers can build these agents for real-time investment analytics, risk management and trading workflows.
In August, LSEG and Rogo announced a collaboration to integrate LSEG’s data with Rogo’s AI platform for investment banks. The combination will allow users to employ Rogo’s AI models and agents to search, analyze and generate insights from LSEG datasets and use them in automating core financial workflows.
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