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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.
For: Managing directors at short-duration private credit and structured finance managers The Job: Identifying corporate treasury desks parking excess cash in yield-enhancing private credit strategies
The prompt
I'm raising for a short-duration private credit strategy positioned as a yield-enhancement alternative to money market funds. Using Dakota Marketplace and web research, identify large non-financial corporations with $1B+ in cash and short-term investments that have disclosed an allocation to private credit or structured products as part of treasury management. Show cash position, treasury or CFO contact, and any recent RFP or manager evaluation activity.
For: Heads of distribution at interval funds and non-traded BDCs targeting the wealth channel The Job: Identifying regional bank trust and wealth management divisions with existing alts due diligence infrastructure
The prompt
I want to get our interval fund in front of bank trust department investment committees. Using Dakota Marketplace, identify regional and super-regional bank trust and wealth management divisions with $5B+ in assets under administration that have existing alternatives due diligence processes and current non-traded BDC or interval fund exposure. Show the head of investments or trust CIO contact and any recent manager additions to their approved list.
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.
For: Heads of institutional sales at private credit managers The Job: Targeting Taft-Hartley health and welfare funds, distinct from their affiliated pension funds, for private credit allocations
The prompt
Using Dakota Marketplace, identify Taft-Hartley health and welfare funds (separate from the affiliated pension fund) with $1B+ in assets that have a documented fixed income or private credit allocation. Show AUM, current allocation percentage, the fund's investment consultant, key trustee or administrator contact, and any recent manager searches.
For: Fundraisers at diversified alternatives managers The Job: Identifying professional sports league player pension funds as a niche, underexplored LP category
The prompt
Using Dakota Marketplace and web research, identify professional sports league player pension and retirement funds (e.g., players' associations) in North America with $500M+ in assets and a documented alternatives allocation. Show AUM, current alternatives allocation percentage, the fund's investment consultant or CIO, and any recent manager commitments in private equity or private credit.
For: Managing directors at middle-market buyout and growth equity funds The Job: Identifying informal family office networks that pool capital for direct co-investment deals alongside GPs
The prompt
I'm raising a middle-market buyout fund and want to tap into family office co-investment clubs that pool capital for direct deals alongside GPs. Using Dakota Marketplace and web research, identify family office networks and co-investment clubs with member AUM totaling $5B+ that have participated in club deals alongside private equity sponsors in the last 3 years. Show typical club check size, the network's lead organizer or contact, and recent deals they've participated in.
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.
Written By: Morgan Holycross, Marketing Manager
Morgan Holycross is a Marketing Manager at Dakota.
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