Data sourced from Dakota Marketplace, the global LP and GP intelligence platform trusted by thousands of investment professionals. Learn More | Book a Demo
Fundraising teams already ask AI assistants real questions: who should we call, who is active right now, and what should I know before Thursday’s meeting. On its own, an AI assistant reasons well but relies on what it can find on the open web, and when we asked one to name the best-fit allocators for a $400m healthcare buyout fund, it couldn’t name a single one.
Dakota Marketplace tracks 21,000+ allocator accounts flagged as private equity investors across seven channels, with 126,500+ direct contacts at those allocators. Connect that data to Claude, ChatGPT, or Copilot, and the same question is answered from curated allocator, contact, commitment, and fund data instead of scattered web results.
In this article, we’ll cover what changes when your AI assistant can see Dakota Marketplace, how the connection works, three real fundraising prompts run with and without the connector, and questions to start with on your own raise.
Why the Data Source Matters
An AI assistant is only as current as what it can read. With web search alone, it can describe the types of allocators that back a strategy, but named allocators, check sizes, and contacts usually sit behind subscription walls. Mandate news arrives as partial roundups, paywalled headlines, and articles from mixed dates.
Connected to Dakota Marketplace, the same assistant answers from curated allocator accounts, titled contacts, dated commitments, public plan minutes, fund and vintage data, and Form D filings, and adds public web sources where they help. Your team keeps the speed of a conversation and gets answers a salesperson can act on.
7 Ways Private Equity Firms Are Using Claude, ChatGPT, and Copilot
1. Building a Target List
The first job of any raise is a list of allocators worth calling. PE teams use AI assistants to turn a fund profile into a ranked, named target list in one prompt.
“I’m raising a $400M lower middle market buyout fund focused on healthcare services. Who are the 10 best-fit allocators in the US to target first, and why? Include their AUM, what they’ve invested in recently, and who I should contact.”
We ran this prompt in Claude on October 23, 2026, twice. Responses are condensed, and the connector works the same way in ChatGPT and Copilot.
With web search only: The assistant said it couldn’t give a verified list from public sources. It described recent healthcare fund closes and who backed them in general terms (“public pension plans, health systems, insurers, endowments”), and noted that named allocators, check sizes, and contacts sat behind subscription walls.
With Dakota Marketplace: It returned ten named allocators with type, AUM, typical commitment, stated interest, and decision-makers. Five of them:
- Adams Street Partners, Chicago: PE fund of funds, $45bn AUM, $20m typical commitment, interested in healthcare, leveraged buyouts, and growth capital. Contact: Partner, Head of Global Buyout Fund Investments.
- Chicago Teachers’ Pension Fund: Public pension, $12.4bn AUM, $12.5m typical commitment, interested in lower middle market and leveraged buyouts. Contact: Chief Investment Officer.
- Wildcat Capital Management, New York: Family office, $3.9bn AUM, $20m typical commitment, investing across venture, growth, and buyout stages. Contact: President and CIO.
- Hersh Family Investments, Dallas: Family office, $3.5bn AUM, $20m typical commitment, interested in healthcare, industrials, and growth businesses. Contact: Managing Director.
- University of Oklahoma Foundation: Endowment, $2.3bn AUM, $12.5m typical commitment, interested in leveraged buyouts and healthcare. Contact: Vice President and CIO.
From there, teams narrow the list by ticket size, add more contacts, or ask which funds each allocator has already backed.
2. Prepping for Allocator Meetings
Meeting prep used to mean an afternoon of annual reports, board packets, and news searches. PE teams now ask for a one-page briefing.
“I have a meeting Thursday with Chicago Teachers’ Pension Fund. Give me a one-page briefing on their private markets allocations, recent commitments, and who I’ll likely be talking to.”
With web search only: The assistant found AUM figures ranging from $9.6bn to about $13bn depending on the article, a few 2025 commitments, and a pending consultant search. Several of the most relevant articles were paywalled, and it couldn’t find the consultant outcome, recent private equity commitments, or the staff you’d meet.
With Dakota Marketplace: One briefing that combined Dakota data with tagged web sources:
- Snapshot: Roughly $12bn to $13bn in assets, a $12.5m typical commitment, and stated interest in lower middle market and leveraged buyouts.
- Recent commitments: $30m to TA Realty Value-Add Fund XIV and $10m to GAP Data Focus Fund II in September 2025, plus a 2025 private equity pacing target of $180m.
- In play now: An MWBE private equity search for a $10m allocation with three named finalists, and an unresolved consultant search for a mandate that covers private equity, private credit, and infrastructure for the first time.
- Who you’ll meet: The Chief Investment Officer and a Portfolio Manager.
- The read: Checks are small and targeted, so lead with fit and track record. With the consultant decision open, direct relationships with staff matter more than usual.
3. Finding Allocators Who Are Active Right Now
Timing wins commitments. PE teams use AI assistants to scan for allocators showing fresh private equity activity, so outreach lands while a plan is deploying.
“Which allocators have shown new activity in private equity in the last 90 days that I should reach out to this week?”
With web search only: Three public pension actions from news coverage, with other articles paywalled or dated 2023 to 2025. There was no complete list, no commitment sizes for most plans, and no sign of who wasn’t buying.
With Dakota Marketplace: Dakota tracked $11.66bn across 180 commitments in August 2026 alone, from 41 allocators, with 52.8% of tracked dollars going to private equity and venture. A sample of the signals:
- Pennsylvania PSERS (August 2026): $500m across four funds, including $150m each to American Industrial Partners IX and Resolute VII.
- Illinois TRS (July 2026): About $790m across nine funds, including $85m to Green Equity Investors X.
- Dallas Police & Fire (October 2026): PE target raised to 11% from 6%, up to $25m to GTCR XV, with mid-market and lower middle market buyouts next.
- Kentucky CERS (September 2026): Weighing $90m to Blue Sea Fund IV, a healthcare-focused buyout fund.
- Quincy and Plymouth County, MA (August 2026): Searching for small and middle market buyout managers at $8m to $15m per manager.
- Milwaukee ERS (September 2026): No new private equity reinvestments planned for 2027.
The last item matters as much as the rest. Knowing who isn’t buying keeps your team from spending a week on a plan that has paused.
Want to see these workflows on your own fund? Book a demo of Dakota Marketplace to get setup with our Claude, ChatGPT, or Copilot connector.
4. Planning a Roadshow
Before a trip, PE teams ask their assistant to group allocators by city so every day is full of meetings that fit the fund.
“Show me New York family offices investing in private equity with more than $1bn in AUM and an average PE ticket above $25m.”
With Dakota data behind it, the assistant can sort allocators by metro area, type, size, and stated interest, then add the contacts at each one. Web directories, by contrast, are rarely organized by city or by what an allocator actually invests in.
5. Researching the Competition
Knowing who else is in market shapes your pitch and your timing. PE teams use AI assistants to map competing funds and see what other investment firms have shown allocators.
“Which middle-market buyout funds with 2025 or 2026 vintages are open for fundraising, and how large are they?”
“What have buyout managers presented to Washington State Investment Board, and what fees did they disclose?”
These answers draw on Dakota’s fund and vintage data, Form D filings, and manager presentations and fee schedules. Dakota tracks 5,253 PE funds open for fundraising, 2,366 of them with a 2025 or 2026 vintage.
6. Keeping Relationships and Contacts Current
People move, and a stale contact list stalls a raise. PE teams ask their assistant to flag changes at the allocators they cover and to check what an allocator already owns.
“Who joined or left private equity teams at the 20 largest US public pensions in the last six months?”
“Which private equity funds has Massachusetts PRIM already committed to, and when?”
Dakota’s contacts are updated by its research team, including job and role changes. Its commitment data shows which funds an allocator has backed and when, including 1,107 PE commitments by public pensions over the past 12 months.
7. Turning Research Into Outreach
The research only pays off when it becomes outreach. Once the list is built, PE teams keep the conversation going: they ask the assistant to draft a first-touch email that references the plan’s last meeting, or to export the list into their CRM workflow.
Teams that also connect their own sources, such as their CRM or firmographic data, can have the assistant combine Dakota Marketplace, their data, and the web in a single briefing.
How to Set It Up
Dakota Marketplace connects to your AI assistant through the Model Context Protocol (MCP), a standard way for an AI model to query an outside system. You sign in with your own Dakota Marketplace credentials, and your assistant runs read-only searches across Dakota’s data each time you ask a question.
The connector works with Claude, ChatGPT, Copilot, and any platform built to support MCP, and it’s included with every Dakota Marketplace subscription. There’s no special syntax to learn: you type the question you’d ask a colleague.
Put Dakota Marketplace to Work Inside Your AI Assistant
Dakota Marketplace gives Claude, ChatGPT, or Copilot access to 21,000+ private equity allocator accounts and 126,500+ direct contacts across seven channels, including 1,420 public pensions, 5,080 family offices, and 3,240 endowments and foundations.
Filter by channel, AUM, metro area, typical PE ticket size, recent commitments, and board-minute activity, then move from research to outreach the same day.
Bring your own fund, segment, or next meeting, and we’ll run it live.
Book a demo of Dakota Marketplace!
