Data sourced from Dakota Marketplace, the global LP and GP intelligence platform trusted by thousands of investment professionals. Learn More | Book a Demo
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 Real Estate Debt Fund II Warehouse Facility Tearsheet Pack
For: Heads of Fundraising at real estate debt fund managers raising a Fund II focused on bridge and transitional lending, prepping for a warehouse facility renewal conversation. The Job: Identifying insurance companies and public pensions with existing real estate debt allocations and recent related commitments, packaged as a tearsheet for a lender update call.
The prompt
I'm raising a $500M Fund II focused on commercial real estate bridge and transitional debt. Using Dakota Marketplace, identify insurance companies and public pensions with $3B or more in AUM that have a documented real estate debt allocation and have made a commitment to a similar strategy in the last 24 months. For each, show AUM, current real estate debt allocation percentage, most recent related commitment, and the two best contacts with title and email. Package as a tearsheet pack for our warehouse lender update call.
2. The New Investment Staff Hire Signal Report
For: Placement agents and heads of business development tracking leadership turnover as a proxy for upcoming manager searches. The Job: Surfacing endowments and foundations that added a new private equity or private credit investment professional in the last six months, flagged by the new hire's background for likely near-term search activity.
The prompt
Using Dakota Marketplace, identify endowments and foundations with $500M to $3B in AUM that have added a new private equity or private credit investment professional in the last 6 months. For each, show the new hire's name, title, prior employer, and the institution's current allocation percentage to that asset class. Flag any where the new hire's background suggests they'll be running near-term manager searches.
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 Direct Lending Competitive Intelligence Brief
For: VPs of Marketing and heads of distribution at private credit funds who need to know which peers are winning mandates in their size range. The Job: Grouping recent public pension direct lending commitments by manager to surface competitive win rates, then flagging allocators who haven't yet committed this cycle as whitespace targets.
The prompt
Using Dakota Marketplace, pull all direct lending commitments made by U.S. public pensions with $10B or more in AUM over the past 18 months. Group by manager to show which firms are winning the most mandates in our size range, then flag any allocators who haven't yet committed to a direct lending strategy this cycle. Those are our best whitespace targets.
4. The Climate Infrastructure Fund ESG Allocator Map
For: Heads of ESG and impact strategy at real assets managers launching a climate-focused infrastructure fund. The Job: Identifying endowments, foundations, and public pensions with a stated net-zero commitment or ESG overlay that also carry an active real assets or infrastructure allocation, with sustainability-specific contacts surfaced where they exist.
The prompt
Using Dakota Marketplace, identify endowments, foundations, and public pensions with a stated net-zero commitment or ESG overlay in their investment policy statement that also have an active real assets or infrastructure allocation. For each, show AUM, real assets allocation percentage, most recent related commitment, and the sustainability or ESG lead contact if one exists separate from the CIO. Package as a briefing doc for our climate infrastructure fund's launch roadshow.
5. The LP Market Trends Narrative for Investor Updates
For: Directors of Marketing at mid-market buyout firms who need a data-backed narrative on where allocator appetite is heading, for use in investor updates and on the firm's website. The Job: Pulling aggregate allocation trends across large public pensions to show how private equity targets have shifted, then translating the data into a market narrative rather than a raw data dump.
The prompt
Using Dakota Marketplace, pull aggregate allocation trends for U.S. public pensions with $5B to $20B in AUM: average private equity target allocation, how it's shifted over the past 24 months, and which sectors are seeing increased commitments. Turn this into a data-backed narrative I can use in our next investor update and on our website.
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.
