Enterprise Knowledge Search
LSEG needed to reduce manual synthesis and fragmented workflows across its financial-data organization while making trusted market data easier for employees and customers to use inside AI workflows.
Reported impact
LSEG accelerated product delivery, cut time-to-market for AI-enabled solutions, improved analyst productivity, and created a governed way to expose trusted financial data inside AI tools that its customers already use.
LSEG paired ChatGPT Enterprise and the OpenAI API with its financial-data platform to change how analysts, product teams, engineers, and business users work. Internally, thousands of employees use the system to summarize market and financial information, draft reports, prototype features, produce client documentation, and streamline operational tasks. Externally, LSEG is using OpenAI to help customers access trusted data in the environments where they already work, including through its Model Context Protocol integration. The company treated this as a governed platform rollout rather than an experimentation program, embedding model-evaluation frameworks, strict privacy and security controls, and human-in-the-loop review for critical outputs from the start. That combination of AI access, trusted data, and enterprise governance shortened product cycles, reduced time from customer request to production, and gave the company a faster path from idea to AI-enabled financial products.
Trusted market and financial data flows into employee workflows through ChatGPT Enterprise and into product or customer workflows through the OpenAI API and Model Context Protocol. Model-evaluation and governance controls sit around those flows, while human reviewers sign off on critical outputs before broader use.
"Accelerated customer delivery timelines to ~4 weeks from request to production"
"LSEG deployed ChatGPT Enterprise and OpenAI APIs across the organization"
"Reduced product release cycles from 3–6 months to 2 weeks"
"combining OpenAI models with LSEG’s trusted data through systems like its Model Context Protocol"
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Scoring methodology
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Traceability
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