Deal Engine was proud to sponsor Intapp Amplify this year, with members of our team attending both the New York and London events.
Across the two conferences, Alex Bajdechi, Steven Kolatac, Phil Westcott, Martin Pomeroy, Sven Hansen and Matthew Kordonowy joined discussions with private markets and technology leaders and partners about how CRM, data infrastructure and AI are evolving across the industry.
This team has worked closely with firms running Intapp DealCloud for many years. That perspective made the conversations across Amplify particularly interesting, as the industry begins to move from experimenting with AI tools towards building the infrastructure that allows AI to operate effectively.
A major focus of the event was Intapp Celeste, Intapp’s new agentic AI layer designed to coordinate AI agents across the private markets workflow. Celeste enables firms to move beyond humans manually operating software interfaces and towards a model where professionals instruct AI agents to complete tasks across their technology stack. In practice, this means agents can interact with systems such as Intapp DealCloud to monitor signals, capture opportunities and automate operational processes.
In this best practice architecture, Deal Engine can provide the integrated market data to the DealCloud environment, the combination forming a firm-owned contextual layer to feed these agents.
Across sessions and conversations with clients, partners and technology leaders, several consistent themes emerged.
The advantage lies in the proprietary market context that those models interrogate. For private markets firms, that context includes their (i) procured market data, (ii) their market context scraping, (iii) their proprietary notes and insight stored in their DealCloud, (iv) their proprietary sourcing history and rationale, (v) their evolving investment thesis and (vi) internal institutional knowledge in their Document Management systems
Many conversations centered on how firms can better integrate and govern this context so that AI can interrogate and drive agentic workflow in a meaningful way.
Another recurring discussion was the move away from adding more standalone tools.
Over time many firms have accumulated complex technology stacks, with different systems managing research, deal flow, market data and internal processes. While each tool serves a purpose, the overall result can be fragmented workflows and disconnected data.
The focus is now shifting towards infrastructure. Firms are thinking more about how their systems and data connect together to form a coherent operating environment that AI can work across.
Several conversations focused on how investment strategy is represented inside technology systems.
Historically, investment theses have often existed as narrative documents or presentations. Increasingly, firms are looking at how those strategies can be translated into the signals and intelligence so that the Frontier AI technology can interpret the market and surface opportunity.
When investment criteria, sector focus and deal characteristics are “bottled” into the intelligence infrastructure, of a firm, the trained agents can guide sourcing workflows, highlight relevant opportunities and support AI driven analysis.
Data governance was another major theme across the event.
Reliable AI outputs depend on reliable inputs. As firms introduce more AI driven capabilities, questions around data structure, permissions and oversight become increasingly important.
Rather than being treated purely as an operational issue, governance and data architecture are becoming core parts of long term AI readiness.
There was strong agreement that AI will not replace the relationship driven nature of private markets.
Instead, the focus is on supplementing existing sourcing approaches and finding the right balance. Relationship networks and inbound opportunities remain essential, but firms are increasingly augmenting these with thesis driven intelligence that can surface opportunities earlier and more consistently.
The goal is not to remove the human element of dealmaking, but to give deal teams better context, more leverage and prioritize where they are spending their time.
One of the more forward looking themes discussed was how professionals may interact with software in the future.
Rather than manually operating multiple applications, the emerging model is one where professionals increasingly instruct AI systems to carry out tasks across those tools on their behalf.
Technologies such as Intapp Celeste reflect this direction of travel, where AI can coordinate activity across different applications while keeping the human in control of the outcome.
For private markets firms, this could gradually reshape how research, origination and internal workflows are managed.
Taken together, the conversations across the New York and London Amplify events pointed to a clear direction of travel.
Frontier AI is advancing quickly, but the firms seeing the most value are those focusing on the foundations. Integrating data, structuring institutional knowledge and ensuring governance across systems are becoming critical steps in making AI useful in practice.
For private markets firms, the most valuable assets remain their people and the knowledge they accumulate over years of investing. When that knowledge is coalesced within a well designed architecture, the organization stands to gain an exponential benefit in future years.
Thank you to the Intapp team for hosting two fantastic market events!
The conversations at Amplify made one thing clear: firms that structure and integrate their market intelligence today will be best positioned to unlock AI tomorrow. Speak with our team to learn more.