PitchBook has launched a federated Microsoft 365 Copilot connector, giving licensed users the ability to interrogate and analyze its vast private capital market datasets directly within Excel using natural language. Announced on June 25, 2026, the integration bridges the gap between one of finance’s most-used research platforms and the ubiquitous spreadsheet tool, promising to accelerate deal analysis, company due diligence, and market trend evaluation without ever leaving the Excel interface.

This marks the latest expansion of Microsoft’s Copilot extensibility model, where third-party data providers can surface their repositories inside the AI assistant already embedded in Word, PowerPoint, Outlook, and most critically for finance professionals, Excel. For the hundreds of thousands of investment bankers, private equity associates, venture capitalists, and corporate development teams that rely on PitchBook for deal sourcing, valuations, and market intelligence, the connector transforms Copilot from a productivity sidekick into a vital research co-pilot.

What PitchBook brings to the table

PitchBook has long been the go-to platform for private market data. Its databases cover millions of companies, investors, funds, deals, and limited partners across the venture capital, private equity, and mergers and acquisitions landscapes. Users trawl through cap tables, fundraising histories, exit valuations, and industry benchmarks to inform investment theses and valuations. Until now, accessing that data typically meant toggling between PitchBook’s web app or API integrations and whatever spreadsheet was being used for modeling.

The new federated connector eliminates that friction. Once an organization has enabled the connector and users have linked their PitchBook and Microsoft 365 Copilot accounts, queries that would have required manual lookups can be phrased as simple prompts. For example: “Show me all Series B biotech companies in the US that raised over $20 million in the last year,” or “Compare the revenue multiples of these five fintech firms against industry medians,” or “Pull the latest funding rounds and lead investors for the companies on this list.” Copilot understands the intent, reaches into PitchBook’s data via the connector, and returns structured information ready for further analysis inside Excel.

How federated connectors work under the hood

Federated connectors are a key part of Microsoft’s strategy to make Copilot more useful across the enterprise software ecosystem. Unlike traditional plug-ins that might perform API calls on behalf of the user and then inject results into the prompt, a federated connector keeps the data source external while allowing Copilot’s orchestrator to plan and execute queries. Crucially, the data does not need to be indexed into Microsoft’s own search graph; instead, the connector serves as a real-time bridge, reducing latency and security concerns.

For organizations worried about data governance, the model preserves the source of truth inside the provider’s environment. When a user asks Copilot in Excel to surface PitchBook data, the query is sent to the PitchBook connector, the connector executes the request against PitchBook’s APIs, and the resulting data is returned directly into the Excel grid—all without Microsoft’s underlying large language model storing or training on that proprietary information. This aligns with how financial firms, especially those subject to strict compliance regimes, prefer to handle sensitive deal data.

The Excel use case: from ad-hoc to always-on

Excel remains the lingua franca of financial analysis. Models, comparables sheets, and waterfall charts are built and shared in Excel daily. By embedding PitchBook access into the Excel Copilot pane, the integration effectively supercharges the hundreds of hours analysts typically spend gathering data. Instead of manually exporting CSVs from PitchBook, cleaning them, and then importing them into a model, an analyst can simply say, “Add the latest total funding and post-money valuation for these Series C companies to the model in column F,” and Copilot does the rest.

Early demonstrations noted by PitchBook suggest that even complex, multi-step data retrieval can be handled conversationally. A user might start with a broad market scan to identify comparable companies, refine the list based on criteria such as “revenue growth above 30%” or “headquarters in California,” and then instantly populate a pre-formatted template with the key metrics. This iterative, dialogue-based approach mirrors the way junior analysts brainstorm with senior bankers—except the data retrieval happens in seconds, not hours.

Moreover, because Copilot in Excel can already generate formulas, charts, and pivot tables, the combined capability means that a single natural language instruction can trigger data acquisition, computation, and visualization in one flow. “Pull PitchBook data for the top 10 European SaaS M&A deals this year and create a bar chart of deal values over time” becomes a feasible single command.

Real-world impact on financial workflows

For private equity and venture capital firms, speed to insight is a competitive advantage. The ability to run scenario analyses on the fly—changing assumptions about funding rounds, market conditions, or exit multiples—while ensuring the underlying data is always current could reshape how investment memos are prepared. Associates often spend half their time on data aggregation; with the connector, much of that labor is offloaded to AI, freeing them to focus on interpretation and strategic recommendations.

Corporate development teams inside large enterprises also stand to benefit. When evaluating acquisition targets, they can now instantly pull comprehensive profiles, funding histories, and investor sentiment data without leaving the Excel workbook already shared with the CIO or CFO. This eliminates version-control headaches and ensures that everyone in the approval chain is looking at the same, real-time data set.

Even limited partners and fund-of-funds managers who track allocations across multiple GPs can use the connector to build dashboards that automatically refresh key metrics like net asset values, commitment pacing, and vintage year performance—all powered by PitchBook’s fund data.

Licensing and availability

The connector is available to mutual customers who hold both an active PitchBook license and a Microsoft 365 Copilot license. It is deployed through the Microsoft 365 admin center, where IT administrators can enable the connector for specific user groups, controlling who can link their accounts. PitchBook’s announcement noted that the connector is included at no additional cost beyond the existing licenses, though precise plan eligibility wasn’t detailed—organizations are advised to check with their PitchBook account managers.

This approach aligns with Microsoft’s broader rollout of Copilot extensibility. Dozens of third-party connectors have been appearing in the Microsoft 365 Copilot ecosystem, from corporate data sources like ServiceNow and Jira to news providers and, increasingly, domain-specific data feeds such as PitchBook. The financial services industry, in particular, has been a prime target given its heavy reliance on external data enriched by AI-driven analysis.

The competitive landscape

PitchBook isn’t alone in exploring AI-augmented financial data access. Rival platforms including Crunchbase, CB Insights, and S&P Capital IQ have been experimenting with natural language interfaces and API plug-ins for AI assistants. However, PitchBook’s move to a federated connector—directly integrated into Copilot’s orchestration rather than as a standalone plug-in—potentially gives it a seamless edge within the Microsoft ecosystem that most finance professionals already inhabit.

Other data providers may follow suit, but establishing these connectors requires deep technical integration with Microsoft’s graph and compliance with strict security protocols—a barrier that incumbents with large engineering teams can more easily surmount. Fornow, PitchBook appears to be first among private capital data providers to offer this level of integration, and it may set a precedent for how specialized research data gets consumed in the age of generative AI.

Addressing potential pitfalls

No AI-powered data integration is without risks. Analyst eyebrows will rightly raise at the prospect of Copilot misinterpreting a query and fetching incorrect or stale data. PitchBook and Microsoft have emphasized that the federated connector respects the data freshness guarantees of the underlying PitchBook platform, meaning the data returned is the same as what a manual user would see at that moment. However, users must still exercise professional skepticism—just as they would when extracting data manually—and double-check critical figures before signing off on a deal term sheet.

Another concern is the black-box nature of how Copilot generates formulas or aggregates data. Microsoft has added transparency features in Copilot that show which data sources were queried and let users inspect the underlying steps. Coupled with the fact that the data lands in Excel’s familiar grid—with full auditability—financial professionals can still trace every number back to its origin.

Data security and privacy remain paramount. By design, no PitchBook data is cached within Microsoft’s AI models; the connector acts as a secure tunnel. Both companies have committed to SOC 2 and ISO 27001 standards, and the integration undergoes regular penetration testing, according to the announcement.

The bigger picture: AI as the new research analyst

The PitchBook connector is emblematic of where enterprise AI is heading. Rather than a monolithic model that knows everything, we’re seeing a network of specialized data providers becoming “plug-ins” to a central reasoning engine. Copilot becomes the interface, orchestrating multiple sources—some internal (your emails, documents, Teams chats) and now external (live market data, company profiles, economic indicators)—to answer complex, multimodal prompts.

For the Windows ecosystem specifically, this illustrates the deepening integration of Microsoft 365 and third-party services. Windows users who spend their days inside Microsoft Edge, Teams, and Office apps are increasingly experiencing a unified AI-assisted workflow. The addition of financial data into that mix turns the operating system into a powerful terminal for financial analysis, not just a window to the web.

Early adopters are already reporting that the combination of natural language query, live data, and Excel’s computational engine feels like “having a supercharged junior analyst who never sleeps.” As the connector rolls out broadly, expect to see templates and best-practice prompt libraries emerge across the private equity and venture capital community.

What’s next?

PitchBook has indicated that this is only the first phase of its Copilot integration. Future enhancements could include linking the connector to Copilot in Word for automated investment memo generation, or to PowerPoint for live-updating pitch decks. The company is also exploring ways to bring PitchBook’s predictive analytics—such as estimated growth metrics and IPO probability scores—directly into the conversational interface.

For Microsoft 365 Copilot, the federated model is proving to be a durable architecture. As more highly-regulated industries adopt AI, the ability to ground responses in vetted, live data sources without creating duplicate copies for indexing will be critical. Expect regulators to take an interest, too; the SEC and other bodies may eventually weigh in on how AI-assisted financial analysis should be documented and audited.

In the near term, though, the message is clear: the days of Alt+Tabbing between a web browser and Excel to manually copy data are numbered. Research is becoming a conversation, and the spreadsheet is both the canvas and the catalyst.