Dun & Bradstreet has revealed that its D&B Commercial Graph™ has been made available via an MCP server from the IBM watsonx Orchestrate Agent Catalog, providing verified commercial context directly into enterprise generative AI workflows. Based on the essential D-U-N-S® Number, it allows autonomous AI agents to get standardized and real-time intelligence about global business identities, corporate affiliations, risk assessment, and payment history for various roles such as sales, marketing, purchasing, compliance, and credit assessment. The solution directly resolves identity fragmentation and data readiness barriers that hinder enterprise generative AI scaling. Emphasizing the foundational necessity of structured data for corporate artificial intelligence adoption, Elizabeth Barrette, General Manager for Master Data Management Solutions at Dun & Bradstreet, stated:
Also Read: SoundHound AI Completes Acquisition of LivePerson
“Enterprise AI delivers its greatest value when it is grounded in trusted business data and context. Bringing the D&B Commercial Graph to IBM watsonx Orchestrate reflects where enterprise AI is headed. The challenge is that most organizations don’t yet have the solid data foundation they need to get the most out of their AI investments. D&B’s recent AI Momentum survey found just 6% of businesses say their enterprise data is fully ready to support AI at scale. Dun & Bradstreet helps close that gap, providing the foundation of continually verified business information required for reliable, traceable AI-driven decisions at scale.” Reinforcing how the integration strengthens enterprise operations, Megan Grant, Managing Director, IBM Technology, U.S. Industry Market, added: “IBM watsonx Orchestrate is designed to connect AI to the systems and data that power the enterprise. By making the D&B Commercial Graph available via MCP, organizations can seamlessly bring their trusted data and business context into the AI workflows they build and deploy.” Ultimately, this collaboration provides enterprises with an audit-ready, agentic architecture that replaces guesswork with validated commercial intelligence, drastically mitigating operational risk and accelerating production-grade AI deployments across global business ecosystems.