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 SFO Growth Equity Map
For: Fundraisers at growth equity firms building a first-pass LP universe for a new fund The Job: Mapping U.S. single-family offices with growth equity appetite, scored by fit and organized by geography
The prompt
I'm raising Fund III for a $1.5B B2B SaaS growth equity firm. Map U.S. Single-Family Offices $500M+ that allocate to growth equity by metro and score them on fit.
2. The Live Deal Comps Table
For: VP-level deal team members at buyout firms running valuation discipline on a live transaction The job: Pulling comparable transactions in the industrial tech space to anchor price discipline before IC
The prompt
I'm a VP on the deal team at a Private Equity firm evaluating a live $400M industrial technology buyout. Using Dakota Marketplace, pull the last 36 months of comparable transactions in the industrial tech / automation space between $200M and $750M enterprise value. Include deal size, EBITDA multiple, buyer, target, and geography. Return a PDF with a comps table, median/mean multiples, and a short narrative on what this means for our price discipline.
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 Post-Close Portco Tech Stack Prospector
For: Account executives selling ERP and finance software to PE-backed portfolio companies The job: Finding portfolio companies that just closed a new transaction and are now in the window where finance and ops modernization decisions get made
The prompt
Show me all private company transactions in the industrials and technology sectors closed in the last 6 months where the deal size was between $50M and $500M.
4. The West Coast Leadership Change Tracker
For: Business development professionals prospecting into LPs where recent leadership changes signal new relationship opportunities The job: Flagging West Coast LPs with recent MD-level or senior investment leadership changes — vacant roles and new hires both
The prompt
Using Dakota Marketplace, show me LPs on the West Coast with managing director or senior investment leadership changes in the last 120 days. Flag vacant roles and recent new hires. Create a PDF.
5. The Financial Sponsors Territory Map
For: Coverage bankers at investment banks building a financial sponsors territory in the Midwest and Southwest The job: Identifying family offices actively deploying PE capital that could be co-investment partners or financing relationships
The prompt
Search Dakota Marketplace for family offices with AUM between $500M and $10B in the Midwest and Southwest that are flagged for private equity focus. I am a financial sponsors coverage banker building my territory map and want to identify family offices that are actively deploying PE capital and may be interested in co-investment opportunities or financing relationships. Pull the firm name, location, AUM, key contact, and co-investment flags.
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.
