Dun & Bradstreet has partnered with OpenAI to bring its D&B Commercial Graph into ChatGPT and Codex, giving finance teams access to Dun & Bradstreet business data inside AI-driven workflows.
Under the arrangement, users can connect Dun & Bradstreet-hosted Model Context Protocol servers to OpenAI's tools. That gives them access to verified business identity, ownership, relationship, credit and risk data through natural-language prompts and custom AI agents.
The setup is intended for tasks such as due diligence, financial reporting, validation, guidance and credit origination. Users can also access Dun & Bradstreet's Finance Analytics tools through the same MCP server framework to support automated business credit decisions with real-time data and a rules-based engine.
The Commercial Graph sits at the centre of the offering. Dun & Bradstreet describes it as a context layer built around the D-U-N-S Number, its long-established business identifier, used to map business identity, ownership links, supplier relationships, financial information and risk indicators across the global economy.
By making that data available in ChatGPT and Codex, the companies are targeting finance functions that increasingly use AI systems for research, assessment and workflow management. The aim is to allow staff to query company records and risk information directly within the tools they already use, rather than switching between separate systems.
The collaboration extends to both smaller firms and large organisations. It is designed for teams that want to use AI in routine finance work while relying on business information that has already been verified and continuously checked.
Data access
Dun & Bradstreet says its Commercial Graph combines public records, proprietary commercial signals, and directly contributed business information. It says that the process creates a continuously validated view of how businesses connect and operate, covering identity data as well as broader ownership and risk indicators.
According to Dun & Bradstreet, the Commercial Graph performs more than 100 billion verifications, tests and checks each month. The company says that scale supports consistency and governance across enterprise systems and AI applications.
For finance teams, the practical use case is direct access to those datasets inside AI tools that can interpret plain-language requests. That could include checking a counterparty's ownership structure, reviewing credit information during an origination process, or bringing external business data into internal reporting and risk reviews.
Dun & Bradstreet says the model also supports what it calls a headless AI architecture, in which finance teams can identify and manage risk across a broader portfolio using automated processes rather than relying solely on traditional front-end software interfaces.
Executive view
Scott Spencer, General Manager, Finance & Credit at Dun & Bradstreet, said the move reflects the growing importance of data quality in AI-driven decision-making.
"AI is quickly becoming a core part of how organizations make decisions across finance, risk, and growth, and its impact depends on the quality of the data behind it," Spencer said. "By bringing the D&B Commercial Graph into ChatGPT and Codex, we're meeting customers where they are working. This helps teams of all sizes, including small and mid-sized businesses, to embrace the power of AI with confidence in their workflows."
The tie-up reflects a wider push by data providers to place structured business information directly into generative AI environments used by professional staff. For vendors such as Dun & Bradstreet, that means positioning proprietary datasets as a source of trusted context for AI systems increasingly used in decision-making.
It also points to the growing use of the Model Context Protocol to connect external data services to AI assistants and coding tools. In this case, the protocol acts as a bridge between Dun & Bradstreet's data infrastructure and OpenAI's products, allowing users to retrieve and apply commercial information without leaving their workflow.
Dun & Bradstreet, founded in 1841, has long been known for business information and credit data services. Its D-U-N-S Number, introduced in 1963, remains widely used as an identifier for commercial entities, and the company is now seeking to extend that role into AI-based finance operations.