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 Private Real Estate Manager Review
For: CIOs at single-family offices conducting a private real estate manager landscape review The Job: Surfacing value-add and opportunistic real estate managers currently fundraising, with fee benchmarks and peer allocation context
The prompt
I'm the CIO of a single-family office (~$1.2B AUM) reviewing the private real estate manager landscape. Particularly value-add and opportunistic strategies, US-focused. Using Dakota Marketplace, surface managers currently fundraising, what comparable family offices have allocated to in this strategy, and any managers appearing in multiple datasets as priority candidates. Include fee benchmarks and flag outliers. Datasets: Form D, Manager Presentations, Family Office Holdings, Fee Studies.
2. The Northeast IR Vacancy Map
For: Executive search consultants building a candidate sourcing list for Head of Global PE/Private Credit searches The job: Identifying consultants and public pensions in the Northeast with open senior alternatives seats
The prompt
Search Dakota Marketplace for institutional allocators in the northeast region — consultants and public pensions with AUM over $1B that have a vacant Head of Global Private Equity or Private Debt (Credit) contact. Show me the account name, type, and AUM. I am building a list to help conduct a search. Create a PDF that I can share with my team.
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 LP Target List
For: Debt capital markets and leveraged finance professionals raising capital for a direct lending fund The job: Building a prospect list of institutions with a demonstrated appetite for private credit
The prompt
Search Dakota Marketplace for institutional allocators — pension funds, endowments, insurance companies, and family offices — with AUM over $1B that have private credit or direct lending in their investment focus. I am raising capital for a direct lending fund and need a prospect list of institutions likely to allocate to private credit strategies. Pull name, AUM, location, and head of alternatives or fixed income contact at each.
4. The Competitor Executive Movement Tracker
For: Deal teams at large growth equity and PE firms tracking talent movement across the competitive landscape The job: Monitoring senior role changes at top competitors to flag implications for deal flow and co-investment relationships
The prompt
I'm on the deal team at a private equity firm. Using Dakota Marketplace, give me a PDF summary of senior investment professional role changes across our top 20 PE/VC competitors in the last 90 days. Flag anyone who joined, left, or was promoted, and note implications for our deal flow and co-investment relationships.
5. The Infrastructure Consultant Target List
For: Fundraisers running consultant relations for a large global infrastructure equity fund The job: Building a prioritized list of OCIOs and consultants with active or upcoming infrastructure mandates before the fundraise heats up
The prompt
I run consultant relations for a global infra equity firm raising a $6B Fund V. Build me a target list of OCIOs and consultants with active or upcoming infra searches, the research head at each, and the firms worth lower-priority touch.
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.
