AI tools like Claude and ChatGPT can now connect directly to databases… and for anyone working in private markets, that's a major unlock.
But only if you're actually using it.
The professionals pulling ahead right now aren't waiting for AI to become part of their firm's official process. They're building it into their daily workflow today whether for meeting prep, prospect research, outreach, or competitive intelligence.
The difference between a generic AI tool and the Claude App connected to Dakota Marketplace is the difference between a guess and a grounded answer.
Generic AI has no access to 30 years of verified LP, GP, fund, and transaction data. It hallucinates. It generalizes.
Dakota Marketplace’s Claude App doesn't return rows. It returns intelligence, built on the only dataset built exclusively for the private markets community.
Here's what that looks like in practice, five things we learned today.
1. The Institutional Hedge Fund Target List
For: Fundraisers raising institutional-quality hedge funds targeting endowments, foundations, and healthcare systems The Job: Identifying the top fifteen U.S. allocators with active hedge fund books and surfacing the right contacts for an institutional-tone intro
The prompt
I'm raising a Tiger-style multi-strat hedge fund. Pull every U.S. endowment, foundation, and healthcare system above $1B with active hedge fund books — top fifteen with CIO, hedge fund PM, and an institutional-tone intro.
2. The Midwest SaaS Founder Outreach Pack
For: Business development and deal sourcing professionals at PE firms covering Midwest middle-market software The job: Building a proprietary outreach pack of SaaS founders and CEOs in the target geography before they're in a formal process
The prompt
I lead Business Development / deal sourcing at a private equity firm covering Midwest U.S. middle-market SaaS. Using Dakota Marketplace, build me a PDF outreach pack of 40 privately held SaaS founders and CEOs headquartered in IL, OH, MI, IN, or WI at firms with estimated revenue between $20M and $100M. Include role, firm, product category, last raise, recommended outreach angle, and any shared network intros available.
These prompts are only as good as the data behind them. Every prompt above runs on Dakota Marketplace data: the verified contacts, AUM, investment preferences, and transaction activity that turn a generic AI answer into a real prospect list. Whichever AI app you use, the facts come from the same place. Book a demo of Dakota Marketplace to get connected.
3. The DIP Lender and Distressed Investor Map
For: Restructuring advisors identifying financing sources for companies entering Chapter 11 The job: Surfacing distressed-focused allocators and family offices that could serve as DIP lenders or distressed debt investors
The prompt
Search Dakota Marketplace for hedge fund-oriented allocators and family offices with AUM over $500M that have a private credit, direct lending, or distressed investment focus. I am advising a company entering Chapter 11 and need to identify potential DIP lenders or distressed debt investors to approach for financing. Pull the organization name, AUM, location, investment focus, and primary credit or alternatives contact.
4. The Emerging Markets PM Talent Pool Scan
For: Associates at executive search firms mapping the available talent pool before formally launching a PM search The job: Identifying Portfolio Managers, CIOs, and Senior Investment Analysts at firms with active EM equity strategies before the search goes live
The prompt
A client asset manager is looking to hire a Portfolio Manager for an emerging markets equity strategy. Before we formally launch, I need to map the available talent pool. Using Dakota Marketplace, find all Portfolio Managers, CIOs, and Senior Investment Analysts at firms with an active emerging markets or global equity strategy and AUM over $1B. Return their name, firm, title, AUM, and direct contact details.
5. The Co-Investment Pipeline Builder
For: Directors of investments at large family offices managing active co-investment programs across asset classes The job: Building a co-investment pipeline from existing GP relationships currently raising follow-on funds, plus a shortlist of new GPs used by peer family offices
The prompt
I run private investments for a $2.5B family office. We co-invest alongside our existing GP relationships across PE, private credit, real estate, and infrastructure. Using Dakota Marketplace, build me a pipeline of co-investment-friendly managers in our existing relationship set who are currently raising follow-on funds, plus a shortlist of new GPs other large family offices use for co-invest. Surface fee discounts on co-invest sleeves where available.
Start Prompting With Real Data
Here's the thing that makes these prompts work… on its own, AI is brilliant at structure and terrible at facts it doesn't have. Ask any chatbot for a pension fund's current allocation, a CIO's contact, or who actually owns a target company, and it will confidently make something up.
That's the whole reason these prompts run on Dakota Marketplace data, no matter which AI app you prefer: you get the speed and structure of AI with contacts, AUM, allocations, and transactions that are actually verified.
AI is the engine. Dakota Marketplace is the fuel.
Connect the two, in Claude, ChatGPT, or whatever you already use, and the work that used to eat your morning takes minutes, with data you can actually act on.
Book a demo of Dakota Marketplace to get started.
