Embedded AI Diligence, Continuation Liquidity Engineering, and Controlled Waterfall Data Infrastructure

Diligence Workflows Move Into Embedded AI Operating Systems

Nasdaq’s acquisition of Dasseti, alongside Datasite’s new embedded AI and Rogo integration, shows private markets diligence shifting from point tools to platform-native workflow automation. Nasdaq is extending eVestment from manager research into AI-enabled DDQs, RFPs, research management, and ongoing monitoring, while Dasseti adds access to roughly 17,000 asset managers and GPs representing about $34 trillion in AUM. Datasite is pushing AI directly into deal rooms for semantic search, summarization, clause extraction, redaction, version comparison, and draft Q&A responses tied to source documents.

Zaigo’s engineering-led AI diligence service and Veridue’s $4 million raise reinforce the same pattern: buyers want systems that test a target’s actual infrastructure, data, workflows, and AI claims before close, not just faster document review. The practical effect is to replace spreadsheet, PDF, and email coordination with embedded systems that standardize inputs and make outputs easier to defend.

For investors and deal teams, the job shifts from manually orchestrating diligence to supervising AI-assisted workflows and validating outputs. Technical fluency in data systems, AI claims, and secure document handling becomes a career advantage as speed alone stops differentiating teams.

Continuation Funds Turn Exits Into Liquidity Engineering

Carrick Capital’s single-asset GP-led continuation vehicle for Saviynt delivered roughly 11x gross and 10x net MOIC on the original investment while letting LPs either cash out or roll. Led by Coller Capital with HSBC Asset Management as co-lead, the deal closed with about $600 million of commitments. Carrick also put in a new $255 million investment as part of Saviynt’s $700 million Series B final close, including support for an employee tender offer, making this a recapitalization and hold-extension rather than a clean sale. Peterson Partners followed the same model with a $510 million continuation fund around Kelso Industries, anchored by more than $450 million from NorthSands Capital.

The market is treating continuation funds as a mainstream liquidity tool, not a niche secondary fix: global volume reached about $71 billion in 2024 and $62.7 billion in 2025, with continuation vehicles accounting for roughly 45% to 60% of secondary deal flow and about 86% of GP-led volume in 2025. For PE and growth teams, that means exits are increasingly structured around rollover economics, secondary pricing, conflict management, and LP elections. The career edge now sits with people who can bridge sale process execution, financing, and investor communication in one transaction.

Continuation Vehicles Turn Liquidity Into an Ownership Tool

On 8 September 2026, Bridgepoint moved about €1.2 billion of senior secured loans from Bridgepoint Direct Lending II into a GP-led credit continuation vehicle anchored by Pantheon Ventures, while Antin launched a similar continuation-style structure for Sølvtrans with GLIL taking a 30% minority stake. Both deals matter because they show continuation vehicles shifting from a niche fix for hard-to-sell assets to a standard way to reset ownership timelines and deliver liquidity without forcing a full exit.

Bridgepoint gave LPs a cash-or-roll choice and kept Bridgepoint Credit managing the assets through realization, extending the life of a diversified European middle-market credit book across healthcare, services, and technology. Antin used the same logic on the equity side: bring in long-term capital, preserve control with founder Roger Halsebakk and family, and support the company’s next growth phase in a less certain market.

For investors and deal teams, this makes liquidity structuring a core skill. The edge now sits with professionals who can model cash-out versus rollover outcomes, assess continuation options alongside exits, and manage the valuation and governance complexity these resets create.

Waterfall Administration Shifts Into Controlled Data Infrastructure

U.S. Bank launched its Private Waterfall Engine this week, an automated platform for private-markets funds that imports upstream data, applies standardized waterfall methodologies, and automates distribution calculations, carried interest, performance-fee administration, reports, and journal entries. The bank says implementation can fall from months to weeks, signaling a move from bespoke spreadsheet models to controlled, systemized fund economics.

For private equity and growth investors, the point is not just speed. Waterfall calculations sit directly on investor outcomes, so automation raises the bar on auditability, consistency, and error reduction across carry and distribution workflows. The platform is aimed at private equity and private credit clients and assumes a workflow built around existing data pipelines, even without named integrations.

For professionals, this shifts value away from hand-built calculations and toward data quality, exception handling, controls, and cross-system coordination. Teams that can manage governance across accounting, reporting, and portfolio data will matter more than teams that can reconcile spreadsheets at quarter-end.