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 looked like in practice this week, five things we learned.
1. The Export Credit Agency Trade Finance List
For: Managing directors at trade finance and supply chain credit funds The Job: Identifying export credit agencies as risk-sharing or co-investment partners for a trade finance strategy
The prompt
I'm raising a trade finance and supply chain credit fund and want to explore export credit agencies as risk-sharing or co-investment partners. Using Dakota Marketplace and web research, identify export credit agencies and government-backed trade finance institutions that have participated in a risk-sharing or co-financing arrangement with a private credit manager in the last 3 years. Show typical facility size, risk-sharing structure, key relationship contact, and recent co-financing deals.
2. The Dutch Pension Fiduciary Manager Infrastructure List
For: Heads of international distribution at infrastructure equity and debt funds The Job: Targeting the fiduciary managers overseeing multiple Dutch pension funds, rather than individual schemes one at a time
The prompt
I'm raising capital from Dutch institutional investors for an infrastructure strategy. Using Dakota Marketplace and web research, identify Dutch pension fund service providers and fiduciary managers that oversee multiple underlying pension funds and have a combined infrastructure allocation above €5B. Show total assets under fiduciary management, infrastructure allocation target, the fiduciary manager's infrastructure research lead, and any recent manager selection processes.
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 Canadian Insurance Company Private Credit List
For: Managing directors at private credit and structured finance managers The Job: Targeting Canadian insurers specifically, distinct from the Canadian pension plans that usually dominate outreach
The prompt
Using Dakota Marketplace and web research, identify Canadian life and P&C insurance companies with CAD $5B+ in invested assets that have a documented private credit or private placement allocation. Show invested assets, current allocation percentage, the CIO or Head of Fixed Income contact, and any recent manager additions in private credit.
4. The SWF Direct Real Estate Co-Investment List
For: Managing directors at core-plus and value-add real estate equity funds The Job: Identifying sovereign wealth funds with direct real estate teams open to co-investing alongside a manager
The prompt
I'm raising Fund V for a core-plus real estate strategy and want to prioritize sovereign wealth funds with direct real estate investment capabilities for co-investment, not just fund commitments. Using Dakota Marketplace, identify SWFs with $30B+ AUM that have a dedicated direct real estate team, showing typical co-investment check size, property type preferences, the head of real estate contact, and any recent co-investments alongside real estate managers.
5. The State Green Bank Co-Investment List
For: Fundraisers at climate infrastructure and clean energy debt funds The Job: Identifying state green banks and infrastructure finance authorities as co-investment or credit enhancement partners
The prompt
I'm raising a clean energy infrastructure debt fund and want to explore state green banks and infrastructure banks as co-investment or credit enhancement partners. Using Dakota Marketplace and web research, identify U.S. state green banks and infrastructure finance authorities with $500M+ in deployable capital that have co-invested or provided credit enhancement alongside a private infrastructure debt manager in the last 3 years. Show deployable capital, typical deal size, key program contact, and recent co-financing activity.
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.
