Dakota Marketplace is the global private markets intelligence platform used by thousands of investment professionals to research LPs, GPs, and private companies — and the data source powering every prompt in this post. Built by fundraisers for fundraisers, Dakota Marketplace delivers complete, accurate, and daily-updated intelligence across every allocator channel — from family offices and RIAs to sovereign wealth funds and public pensions. 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 looks like in practice, five things we learned today.
1. The Infrastructure Debt Fund LP Prospect List
For: Directors in Infrastructure Debt Capital Markets at investment banks placing infrastructure debt funds with institutional allocators. The Job: Identifying insurance companies, corporate pensions, sovereign wealth funds, and large family offices with existing infrastructure debt allocations and no known relationship with the manager being placed
The prompt
I'm a Director in Infrastructure Debt Capital Markets at a mid-size investment bank. My client is raising a $1.5B infrastructure debt fund targeting U.S. and European core infrastructure assets. Using Dakota Marketplace, identify institutional allocators — insurance companies, corporate pensions, sovereign wealth funds, and large family offices — with AUM over $2B that have an existing infrastructure debt or core infrastructure allocation and made a new real assets or infrastructure commitment in the last 24 months. Include the head of infrastructure, head of fixed income, or CIO at each institution, their preferred deal structure (closed-end vs. open-end), typical ticket size, and geographic focus. Prioritize accounts with no known relationship with this manager and return a ranked LP prospect list as a PDF.
2. The Insurance Company LP Target List
For: Managing Directors of Capital Formation at real assets managers raising a new fund with limited insurance company LP relationships. The Job: Building a ranked insurance company prospect list across North America and Europe with confirmed real assets or private credit allocations, flagging recent commitment activity and gatekeeper relationships
The prompt
I'm raising Fund IV for a $3B real assets manager focused on infrastructure and real estate debt strategies. We've had strong success with pension funds and endowments but have almost no insurance company LPs. Using Dakota Marketplace, pull all insurance companies in North America and Europe with AUM over $5B that have an allocation to real assets, infrastructure, or private credit. For each, show the organization name, AUM, location, key investment decision-makers with titles and direct contact info, any recent mandates or commitments to real assets strategies, and whether they have an existing relationship with a placement agent or gatekeeper. Rank the list by AUM and flag any that have made a new commitment to a strategy in our category in the last 18 months.
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 PE-Backed Industrial CFO Candidate Longlist
For: Partners at private markets executive search firms running retained CFO mandates for PE-sponsored industrial distribution and services companies. The Job: Mapping the full CFO and VP Finance talent pool across PE-backed industrial distribution companies, flagging executives with long tenure or recent transaction exposure as highest-priority candidates
The prompt
From Dakota Marketplace, pull all CFOs and VP Finance / Finance Directors currently employed at PE-sponsored industrial distribution or industrial services companies with estimated revenues between $50M and $500M. I am conducting a retained CFO search and need to build a candidate longlist. For each contact, return: full name, current company, title, years in current role, prior employer(s), educational background where available, and email or LinkedIn contact information. Flag any executives who have been in their current role for more than 4 years or whose company completed a transaction in the past 12 months.
4. The Emerging Market PE Manager Vetting Report
For: Heads of Alternatives at sovereign wealth funds expanding emerging market private equity allocations and evaluating first- and second-time managers with regional specialization. The Job: Identifying Southeast Asia and Latin America-focused PE managers currently fundraising with institutional LP validation, performance benchmarks, and peer sovereign wealth fund commitment history
The prompt
I'm the Head of Alternatives at a $30B sovereign wealth fund expanding our emerging markets private equity allocation from 5% to 10% of the alternatives portfolio. We want to add 2-3 new first-time or second-time EM PE managers with regional specialization in Southeast Asia or Latin America. Using Dakota Marketplace, identify EM-focused PE managers currently fundraising with AUM between $300M and $2B and a track record of at least one prior fund. Show peer commitments from other sovereign wealth funds, university endowments, and large pension funds in the last 18 months. Include managing partner or IR contact, fund size and target close date, strategy focus, and available performance benchmarks (IRR, TVPI, DPI). Prioritize managers with 3+ institutional LP commitments already confirmed and return a PDF for our investment committee.
5. The Multi-Strategy RIA Compliance Prospect List
For: Enterprise Account Executives at compliance and regulatory reporting software companies targeting SEC-registered investment advisers expanding into private markets. The Job: Finding multi-strategy RIAs that have recently added a private fund — the clearest trigger event for outgrowing manual Form ADV and GIPS compliance workflows
The prompt
I sell compliance and regulatory reporting software to SEC-registered investment advisers. Using Dakota Marketplace, find all registered investment advisers in the United States with AUM between $500M and $5B that manage a combination of liquid equity or fixed income strategies and at least one private fund or alternative product. These multi-strategy RIAs face the most complex Form ADV and GIPS reporting requirements and are most likely to be outgrowing manual compliance workflows. Include firm name, AUM, number of strategies or funds on record, CCO or head of compliance contact, and location. Prioritize firms that have added a new private fund in the last 24 months — a clear compliance infrastructure trigger event. Return a ranked outreach list of 40 priority 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.
