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 Hedge Fund Platform Consultant-Gated Pension List
For: Heads of institutional sales at multi-manager hedge fund platforms The Job: Mapping which target pensions access hedge funds through a consultant, and whether that consultant has an open search
The prompt
I run distribution for a multi-manager hedge fund platform and most of our target pensions only access hedge funds through a consultant. Using Dakota Marketplace, identify U.S. public pensions above $5B with hedge fund allocations that use an investment consultant, show which consultant is of record, the consultant's hedge fund research lead, and whether the plan has an open or upcoming hedge fund search.
2. The Diverse Manager Program Targeting List
For: Managing directors at diverse-owned lower middle-market buyout firms The Job: Identifying LPs with a formal emerging manager or diverse manager program ahead of a Fund II raise
The prompt
I run a diverse-owned lower middle-market buyout firm raising Fund II. Using Dakota Marketplace, identify public pensions, endowments, and foundations with an active emerging manager or diverse manager program, showing program AUM carve-out, check size range, program contact, and any recent diverse manager commitments. Prioritize plans with a formal MWBE or emerging manager policy.
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 Real Assets Conference Tearsheet Pack
For: Managing directors at timber and farmland funds The Job: Building tearsheets on natural resources-allocating institutions before an institutional real assets summit
The prompt
I'm attending an institutional real assets conference next month. Using Dakota Marketplace, build tearsheets on the endowments, foundations, and pensions on the attendee list that have a natural resources or farmland allocation above 2%, including AUM, current managers in the space, and the best contact to request a meeting with on-site.
4. The Healthcare-Focused Growth Equity List
For: Heads of IR at healthcare-focused growth equity funds The Job: Targeting health systems and medical endowments with existing growth equity exposure ahead of a Fund II raise
The prompt
I'm raising Fund II for a healthcare-focused growth equity strategy. Using Dakota Marketplace, identify healthcare systems, medical center endowments, and health conversion foundations with $500M+ in investable assets and an existing private equity or growth equity allocation. Show AUM, PE allocation percentage, CIO contact, and any recent healthcare-sector-specific manager commitments.
5. The Secondaries Fund LP Cadence Tracker
For: Directors of IR at private equity secondaries funds The Job: Flagging warm pipeline accounts that have gone quiet, ranked by AUM, with a re-engagement note ready to send
The prompt
Pull every account in our Dakota-tracked pipeline tagged as "warm" or "active prospect" for our secondaries fund that hasn't had a logged touchpoint in 60 days. Show AUM, secondaries program size, last contact date, and primary contact. Rank by AUM and draft a two-sentence re-engagement note referencing their most recent secondary transaction.
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.
