Dun & Bradstreet's Graph Connector is now live inside Microsoft 365 Copilot, the company confirmed on June 2, 2026. The integration gives developers and enterprise users no-cost access to a curated sample of verified business data, plumbed directly into the AI assistant that lives across Word, Excel, Teams, and the rest of the Microsoft 365 suite. The move signals a significant expansion of Copilot’s data-gathering reach—and a tighter embrace of third-party knowledge graphs that promise to turn the chatbot into a genuinely enterprise-grade research tool.

Graph Connectors are the plumbing that channels external data into Microsoft Graph, the semantic fabric that powers search, recommendations, and now Copilot’s large language model–backed responses. Instead of relying solely on your own tenant’s documents, emails, and chats, a Graph Connector lets the system index and retrieve information from line-of-business systems, data warehouses, or third-party services. Microsoft has been steadily expanding the catalog of first-party connectors for tools like ServiceNow, Salesforce, and Jira. But the arrival of a data specialist like Dun & Bradstreet—a firm with a 180-year history of compiling and verifying business intelligence—marks a new tier of rich, externally validated content that Copilot can instantly surface.

Dun & Bradstreet’s connector brings a carefully curated slice of its global business database into the Microsoft 365 environment. The no-cost sample includes verified company names, addresses, industry codes, key financial metrics, ownership hierarchies, and firmographic attributes. For a developer building a Copilot-powered app or an enterprise architect evaluating the technology, this sample functions as a sandbox: you can craft prompts that pull up a supplier’s credit rating, explore a competitor’s corporate family tree, or produce a report comparing revenue figures across a sector—all without writing a single line of integration code. The data is pre-indexed and ready to be queried through natural language.

From the user’s perspective, the experience is seamless. An employee drafting a vendor risk assessment in Word can ask Copilot, “What is the Dun & Bradstreet credit score and payment history for Acme Corp?” and receive a cited answer drawn directly from the connector’s index. In Excel, that same person can instruct Copilot to “list all subsidiaries of GlobalTech Ltd. with their annual revenue and employee counts,” and the assistant populates a table with D&B-verified figures. In a Teams meeting, a quick “show me background on the new prospect’s parent company” can pull up a summary card. Because the data originates from Dun & Bradstreet’s vetted repository, users can trust it more than a generic web search—and that trust is the connector’s true currency.

Behind the scenes, the integration leverages Microsoft’s semantic indexing and vector embedding technologies. When the connector is configured by an administrator—who must have the appropriate licenses and permissions—it syncs a predefined dataset into the tenant’s Graph. That data is then processed by the semantic index, which understands relationships, synonyms, and entity linkages. When a user prompt invokes the connector, Copilot’s orchestrator reasons over both the internal tenant data and the external D&B index, merging sources and ranking them by relevance. Security boundaries remain intact: only users who have been granted access to the connector’s data can retrieve it, and the data itself is subject to the same compliance and governance controls that apply to all Graph content.

For developers, this is a significant shortcut. Building a custom connection to the Dun & Bradstreet API typically requires backend development, authentication management, and mapping of the data model to application-specific schemas. The ready-made connector abstracts all of that. Developers can jump straight to building intelligent prompts, creating plugins that combine D&B data with predictive models, or embedding verified company profiles into line-of-business applications via Copilot extensibility. The no-cost sample gives them a realistic dataset—not just a handful of dummy records—so they can test accuracy, performance, and user experience before committing to a commercial agreement with Dun & Bradstreet for the full dataset.

Enterprise users stand to gain immediate productivity improvements. Research that once meant switching between a CRM, a browser, and a Bloomberg terminal can now happen inside the flow of a document or a chat. Sales teams can prepare for calls by asking Copilot to generate a briefing note with the prospect’s financial health and recent news, all sourced from D&B. Procurement departments can rapidly verify vendor details during onboarding. Legal and compliance teams can cross-reference company data against sanctions lists without leaving Microsoft 365. Because the data is updated regularly—Dun & Bradstreet maintains one of the world’s most frequently refreshed business databases—the risk of acting on stale information drops considerably.

The announcement also underscores Microsoft’s broader strategy of turning Copilot into an aggregation point for authoritative data. Earlier in 2026, the company integrated the Knowledge Graph from LinkedIn and expanded its SAP connector. The Dun & Bradstreet connector, however, is particularly notable because the company’s D‑U‑N‑S Number is effectively a global standard for identifying legal entities. Embedding D-U-N-S–based lookups into Copilot means that every query can be pinned to a unique, persistent identifier, reducing ambiguity when major corporations have similar names or operate through dozens of subsidiaries. This entity resolution capability is something that consumer web search still struggles with, but an enterprise-grade AI assistant can finally deliver.

Analysts point out that the move accelerates the “bring your own data” trend in generative AI. Rather than fine-tuning a model on proprietary figures—an expensive and operationally complex process—organizations can now inject trusted, structured data directly into the retrieval-augmented generation (RAG) pipeline that Copilot already uses. The connector approach also sidesteps some of the token-window limitations of large language models, because only the most relevant data is surfaced at query time, not the entire dataset. This makes the system both faster and more cost-effective at scale.

Still, the no-cost sample has limitations. It does not include Dun & Bradstreet’s entire 500-million-record database; the sample is limited to a subset of companies, likely those with publicly available core data. Users who need deeper financials, predictive risk scores, or real‑time monitoring will eventually need a commercial license. The connector also requires that the tenant has a Microsoft 365 Copilot license and an administrator who can set up the connection through the Microsoft 365 Admin Center. Some organizations may balk at the governance overhead, especially in highly regulated industries where external data ingestion must be audited thoroughly. Microsoft and Dun & Bradstreet have published documentation outlining the data lineage and access-control model, but as with any Graph Connector, IT teams will want to run a proof of concept before rolling it out enterprise-wide.

Feedback from early testers has been largely positive. Developers on the Microsoft 365 community forums have praised the speed of integration and the quality of the curated sample. A few have noted that the initial sync can take several hours for larger tenants, and that occasional mismatches between the sample’s industry codes and a company’s self-described sector can result in slightly off responses. These are quibbles that Dun & Bradstreet has acknowledged and is working to refine in subsequent data updates. Overall, the reception suggests that the market is hungry for authoritative external data that can be consumed without leaving the Microsoft 365 shell.

Looking ahead, the partnership is likely to expand. Dun & Bradstreet has already hinted at plans to offer premium connector tiers that unlock its full D&B Hoovers, ESG, and supply chain risk data. Microsoft, for its part, is encouraging other data providers to follow suit. The connector marketplace within Microsoft 365 is evolving into a data supermarket, and the presence of a heavyweight like D&B validates the model. For companies that rely on accurate business intelligence, the connector represents a quiet revolution: suddenly, the AI assistant that drafts emails and summarizes meetings is also a direct pipeline to one of the world’s most comprehensive troves of company information.

In the immediate term, organizations that have been waiting for a low-risk way to experiment with Copilot’s external data capabilities now have a concrete on-ramp. They can test how AI-enriched workflows handle real business data, measure the impact on productivity, and decide whether to invest in the full-scale service. Given that this on-ramp costs nothing beyond the existing Copilot subscription, the barrier to entry is negligible. As enterprise AI matures, the ability to seamlessly weave third-party knowledge into everyday tasks will separate leading organizations from those still wading through browser tabs. The Dun & Bradstreet Graph Connector in Microsoft 365 Copilot is poised to be one of those subtle but essential upgrades that rewires how business gets done.