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 Canadian Pension Roadshow Tearsheet Pack
For: Managing directors of institutional sales at real assets strategies preparing for a Toronto roadshow The Job: Building a tearsheet pack on Canada's largest pension plans with infrastructure and real assets allocation appetite before the flight over
The prompt
I'm traveling to Toronto next month to meet with Canada's largest pension plans. Using Dakota Marketplace, build a tearsheet for each of the top Canadian pension plans with a stated infrastructure or real assets allocation, including total AUM, current real assets allocation percentage and target, most recent external manager commitments in the asset class, and the names and titles of the relevant investment team contacts. Flag any plans that have publicly signaled interest in increasing real assets exposure in 2026. Package this as a tearsheet pack I can review on the flight over.
2. The Foundation Conference Tearsheet Pack
For: Heads of institutional relationships at impact-focused private equity funds attending the Council on Foundations annual conference The Job: Building tearsheets on the largest health and community foundations with PE and impact investing allocations before the first meeting
The prompt
I'm attending the Council on Foundations annual conference next month and want to prepare for meetings with the largest health and community foundations on the attendee list. Using Dakota Marketplace, build a tearsheet for each of the top foundations with $500M or more in assets that have documented private equity or impact-investing allocations. For each foundation, include total AUM, current private equity allocation percentage and target, most recent commitment to an outside manager, key contacts (CIO and Director of Investments) with titles and email, and notes on their approach to mission-aligned or impact investing. Package this as a tearsheet pack I can review on the flight to the conference.
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 Insurance Company Structured Credit Tearsheet Pack
For: Heads of insurance solutions at structured credit managers attending the NAIC insurance investment conference The Job: Building tearsheets on insurance general accounts with active structured credit allocations before the conference
The prompt
I'm attending the NAIC insurance investment conference next month and want tearsheets on the insurance companies most likely to add structured credit exposure. Using Dakota Marketplace, identify the top 6 insurance company general accounts with $2B or more in invested assets that have documented structured credit, CLO, or securitized allocations. For each, include total invested assets, current structured credit allocation percentage and target, most recent manager addition or RFP, key contacts (Chief Investment Officer and Head of Fixed Income) with title and email, and notes on their approach to rating agency capital charge considerations. Package this as a tearsheet pack I can review before the conference.
4. The Taft-Hartley Infrastructure Tearsheet Pack
For: SVPs of business development at infrastructure debt funds attending the national Taft-Hartley trustees conference The Job: Building tearsheets on the largest multiemployer pension plans with documented infrastructure and real assets allocations before the conference
The prompt
I'm attending the national Taft-Hartley trustees conference next month and want tearsheets ready before I go. Using Dakota Marketplace, build a tearsheet for each of the top multiemployer Taft-Hartley pension plans with $2B or more in AUM that have a documented allocation to infrastructure, real assets, or private credit. For each plan, include total AUM, current infrastructure/real assets allocation percentage and target, most recent external manager commitment in that asset class, the names and titles of the fund's investment consultant and key trustee or investment staff contact, and any recent plan minutes referencing infrastructure or private credit manager searches. Package this as a tearsheet pack I can review on the flight to the conference.
5. The Private Credit Summit Tearsheet Pack
For: Heads of institutional relationships at multi-strategy private credit managers attending the Institutional Private Credit & Alternative Credit Summit The Job: Building tearsheets on endowments, foundations, and public pensions actively expanding private credit allocations or running an open manager search before the summit
The prompt
I'm attending the Institutional Private Credit & Alternative Credit Summit next month and want tearsheets ready before I go. Using Dakota Marketplace, build a tearsheet for each of the top endowments, foundations, and public pension funds with $1B or more in AUM that have increased their private credit allocation by at least 3 percentage points in the last 18 months or have an open manager search for direct lending or structured credit. For each institution, include total AUM, current and target private credit allocation percentages, most recent commitment to a private credit manager, the names and titles of the relevant investment staff contacts, and any recent board or investment committee commentary on private credit strategy. Package this as a tearsheet pack organized by institution type that I can review on the flight to the summit.
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.
