NEW YORK — S&P Global has announced the launch of its AI Data Portal and Adaptive Retrieval, introducing what the company describes as the industry’s first unified solution that combines Adaptive Retrieval and Deterministic Retrieval for enterprise AI applications.
The new platform is designed to give AI agents and large language models (LLMs) direct access to licensed S&P Global data using natural language, while ensuring information remains trusted, cited, verifiable, and auditable.
According to the company, the launch reflects the rapid evolution of AI in financial services—from controlled automation to autonomous multi-agent systems capable of executing complex analytical tasks.
A New Era of AI-Powered Financial Intelligence
Unlike traditional retrieval methods, Adaptive Retrieval enables AI systems to search, assemble, and connect information across multiple S&P Global datasets simultaneously. The technology is designed for complex workflows such as research, investment analysis, and report generation.
Meanwhile, Deterministic Retrieval, powered by the Kensho LLM-ready API introduced in 2025, continues to provide structured, API-driven access for focused analytical tasks, including company research and earnings transcript analysis.
Together, both capabilities are now integrated into the S&P Global AI Data Portal, allowing organizations to choose the retrieval model that best fits their AI architecture.
S&P Global: AI Workflows Are Evolving Rapidly
Sally Moore, Chief Client Officer and Co-Head of Market Intelligence, emphasized the growing importance of flexible AI infrastructure:
“The use of AI in financial services is rapidly accelerating and evolving, from tightly controlled workflows to fully autonomous, multi-agent systems.”
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She added:
“With Deterministic and Adaptive Retrieval now available together, we’re ensuring that S&P Global’s trusted data is accessible across that full range of workflows, so customers can access data the way they need it today and adapt as their architectures evolve.”
Solving One of Enterprise AI’s Biggest Challenges
As organizations increasingly rely on AI-driven decision-making, enterprise data requirements have fundamentally changed.
Rather than simply accessing information, AI systems now require high-quality, licensed data that is properly cited, verifiable, and auditable.
S&P Global says its new platform removes much of the engineering complexity traditionally required to connect trusted enterprise data into AI systems, allowing organizations to focus on building AI applications instead of managing data infrastructure.
Building the Foundation for AI-Native Financial Workflows
Bhavesh Dayalji, Head of Kensho Data & Intelligence, believes the announcement represents only the beginning of a broader transformation.
“For S&P Global, the data retrieval layer is only the beginning. Cited, verifiable S&P Global data provides the trusted foundation on which higher-value AI-native experiences can be built.”
He continued:
“Now, S&P Global data flows directly into the tools and platforms where customers work through financial skills and plugins, and MCP apps that allow customers to visualize, explore, and interact with S&P Global data inside AI applications. This work continues as we develop additional workflow solutions and AI-native experiences that put trusted data at the center of how customers work with AI and multi-agent systems.”
Why It Matters
The announcement highlights a significant shift in enterprise AI strategy.
Competitive advantage is no longer determined solely by the sophistication of large language models, but increasingly by the ability to connect those models with trusted, licensed, and verifiable enterprise data.
With the launch of the AI Data Portal, S&P Global is positioning itself not simply as a financial data provider, but as a foundational infrastructure partner for the next generation of AI-powered financial services.
Source: S&P Global Press Release (via PR Newswire), July 21, 2026.
