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 CIO Succession Candidate Map
For: Senior consultants leading confidential executive searches at institutional allocators The Job: Building an initial candidate universe for a CIO search at a mid-sized public pension
The prompt
I'm leading a confidential executive search for a CIO role at a $4B public pension in the Midwest. Using Dakota Marketplace, find all individuals currently listed as CIO, Deputy CIO, or Chief Investment Strategist at public pension funds, endowments, or foundations with AUM between $1B and $10B in the Midwest and Great Plains. Return their full name, current firm, AUM, email, and phone so I can begin initial outreach.
2. The Hedge Fund Manager Shortlist for a Multi-Family Office
For: Heads of manager research at multi-family offices conducting hedge fund manager diligence The job: Identifying actively raising hedge fund managers across key strategies with appropriate minimums and capacity context
The prompt
I'm the Head of Manager Research at a multi-family office serving 60+ UHNW client families. Using Dakota Marketplace, identify hedge fund managers actively raising capital across long/short equity, global macro, and multi-strategy. I want to know which managers other family offices have allocated to in the last 18 months, minimum investment thresholds suitable for our smallest qualified-purchaser clients (~$5M ticket), and any capacity-constrained managers we should approach now.
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 Scaling GP Outreach List for IR Software
For: Sales directors at IR and LP reporting software companies targeting mid-market GPs closing new funds The job: Finding PE and VC firms that are scaling operations and likely outgrowing spreadsheet-based LP management
The prompt
Using Dakota Marketplace, find private equity and venture capital firms in North America with AUM between $500M and $3B that have filed a Form D in the last 12 months. Identify firms raising a Fund II, III, or IV — suggesting they are scaling operations and likely outgrowing spreadsheet-based LP management. Include firm name, AUM, fund name, strategy focus, and CFO or COO contact at each. Return a ranked outreach list of the top 30 prospects, prioritizing firms with the most recent Form D activity and multiple funds on record.
4. The Family Office Manual Workflow Prospector
For: Regional sales directors selling IR and CRM software to family offices and boutique managers The job: Identifying Northeast family offices managing alternatives that are likely running on outdated systems
The prompt
I sell investor relations and CRM software to family offices and boutique investment managers. Using Dakota Marketplace, find all single-family offices and multi-family offices with AUM between $500M and $5B in the Northeast that manage alternatives allocations. Show me the key operations or technology contact at each firm, their AUM, city, and employee count. I want to build an outreach list of firms likely running on spreadsheets or outdated systems that would benefit from a modern IR platform.
5. The Public Pension Real Estate Debt Coverage Map
For: Distribution leaders at real estate debt managers building a systematic public pension coverage strategy The job: Identifying every U.S. public pension with real estate debt eligibility above $10B, with consultant of record, PM contact, and recommended outreach cadence
The prompt
I run distribution at a $7B real estate debt manager. Pull every U.S. public pension above $10B with real estate debt eligibility, show me the consultant of record and PM at each, and tell me what the right cadence looks like.
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.
