At the investor day there were comments made on evolving the pricing model for PitchBook. How do AI-enabled products and data fit into this model? Are customers looking for more value at the current price point or are they willing to pay more to get access to the company's AI-enabled products and data?

At the investor day there were comments made on evolving the pricing model for PitchBook. How do AI-enabled products and data fit into this model? Are customers looking for more value at the current price point or are they willing to pay more to get access to the company's AI-enabled products and data? We're evolving PitchBook's pricing to reflect how clients can increasingly derive value, not only through the platform, but also through data and intellectual property (IP) accessed via large language model (LLM) integrations and Model Context Protocol (MCP) connectors. This is fundamentally about capturing the value of the workflow and IP layer, not just data access: Proprietary tools like the VC Exit Predictor, Manager Scores, and Valuation Estimates remain platform-exclusive, and that's deliberate, because the PitchBook platform is where we believe switching costs are highest. We expect that some clients prefer seat-based licenses while others are shifting toward value- or consumption-based models. We intend to price to capture the value delivered across both and we're early in this transition. Clients have told us pricing certainty matters, so we're testing structures that can balance flexibility with predictability.