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 LP Re-Engagement Priority List
For: Directors of IR at mid-market buyout firms managing active prospect pipelines The Job: Surfacing LP accounts that have gone cold and ranking them for re-engagement by AUM
The prompt
I'm a Director of IR at a mid-market buyout firm. Pull up all LP accounts in our pipeline marked 'Active Prospect' that haven't had a logged meeting or call in the last 90 days. For each, show me the AUM, last contact date, primary contact name and title, and which fund they're evaluating. Rank by AUM descending so I can prioritize re-engagement and prep tailored follow-up talking points for each.
2. The Direct Lending Universe for Sponsor-Backed Deals
For: Capital markets professionals at large PE firms supporting deal teams on financing decisions The job: Mapping the current unitranche and direct lending landscape for mid-to-large sponsor-backed transactions
The prompt
I run Capital Markets at a private equity supporting our PE deal teams. Using Dakota Marketplace, give me a PDF of the current unitranche and direct lending universe for U.S. sponsor-backed deals between $250M and $1B. Include active lenders, recent closed financings in the last 6 months, pricing (spread/OID) where available, typical hold sizes, and key relationship contacts to call for the next deal.
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 GP-Led Secondary Buyer Universe
For: Managing directors at secondary advisory firms running GP-led continuation vehicle processes The job: Building a targeted buyer universe for a 2018-vintage mid-market PE fund seeking a GP-led secondary
The prompt
I'm running a GP-led secondary process for a 2018-vintage mid-market private equity fund. Using Dakota Marketplace, find all fund-of-funds, dedicated secondaries buyers, and endowments with known secondary PE mandates and AUM over $1B. Include the primary investment contact name, title, email, phone, and any notes on secondary appetite. Prioritize accounts in the Northeast and Mid-Atlantic.
4. The PE-Backed COO Candidate Universe
For: Senior associates at executive search firms conducting confidential COO searches for PE-backed companies preparing for exit The job: Mapping senior operations leaders at PE-sponsored logistics and supply chain tech companies with exit experience
The prompt
I'm conducting a confidential COO search for a $200M ARR PE-backed logistics technology company in the Midwest preparing for an eventual exit. Using Dakota Marketplace, identify senior operations leaders — COOs and EVPs of Operations — currently at PE-sponsored logistics, supply chain, or transportation technology companies with revenue between $100M and $500M. Include their current employer, PE sponsor, tenure in role, and direct contact information. Flag candidates who have navigated a company through a PE exit or sale in the past 5 years — those are my highest-priority targets. Return as a ranked PDF.
5. The Multi-Fund GP Back-Office Prospect List
For: Account executives selling fund administration and back-office software to PE and VC firms The job: Identifying GPs with multiple active funds that are most likely outgrowing manual back-office processes
The prompt
I sell fund administration and back-office software to PE and VC firms. Using Dakota Marketplace, find all private equity and venture capital firms with AUM between $500M and $3B in the United States that have filed Form D filings on two or more funds in the last three years. Show me the CFO or COO contact at each firm, plus AUM, fund count, and location. These firms are likely outgrowing spreadsheet-based administration and are ideal prospects.
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.
