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 Post-Conference Follow-Up Prioritization Engine
For: VPs of institutional distribution at real assets funds returning from a major LP conference with 40 meetings in three days The Job: Cross-referencing every meeting against the CRM, validating contacts, surfacing open mandates, flagging competitor commitments, and drafting re-engagement notes for the top 15
The prompt
I just returned from iConnections Global Alts. I met with roughly 40 LPs over three days. Using Dakota Marketplace, cross-reference the following list of institutions I met with against our full CRM. For each institution: (1) confirm the decision-maker I met is the right primary contact or flag if there's a more senior contact on the platform, (2) show their current real assets allocation and AUM, (3) identify whether they have any open mandates or recent RFPs in infrastructure or real assets, and (4) flag any that have committed to a competitor fund in the last 18 months. Prioritize the top 15 for immediate follow-up based on fit and recency of activity, and draft a one-line re-engagement note for each.
2. The Founder-Led Healthcare Services Deal Sourcing Screen
For: Principals at growth equity firms sourcing non-sponsored healthcare services companies for a growth equity investment or platform build The Job: Identifying founder-owned healthcare services companies in the Southeast and Midwest with meaningful revenue and long-tenured CEOs most open to a minority growth partner conversation
The prompt
Using Dakota Marketplace, search for healthcare services companies that: (1) are NOT currently sponsor-backed (founder-owned or PE-exited and re-independent), (2) have estimated revenue between $20M and $150M, (3) are headquartered in the Southeast or Midwest US, (4) operate in home health, behavioral health, specialty pharmacy, or outpatient surgical services. For each result, show: company name, subsector, HQ city and state, estimated revenue, founder/CEO name and direct email, CFO name if available, headcount estimate, and any known capital raise history. Flag companies where the CEO has been in role for more than 8 years — long-tenured founders are often most open to a minority growth partner conversation.
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 Climate Tech VC Manager Screen for a New Thematic Sleeve
For: Senior investment officers at university endowments building a new thematic allocation to climate technology and energy transition The Job: Identifying VC managers in climate tech with the right fund size, vintage, and GP pedigree — prioritizing those pre-first close for better LP terms
The prompt
Using Dakota Marketplace, find venture capital managers with the following profile: (1) primary investment focus is climate technology, energy transition, clean energy, or sustainability, (2) most recent fund size is between $100M and $750M, (3) fund vintage 2021 or later, (4) GP team has at least one partner with a prior institutional investment or operating background. For each manager, return: firm name, fund name and size, vintage year, strategy description, GP team bios (titles, backgrounds), key contact name and email, current fundraise status, any university endowment LPs already in the fund (helpful for reference calls), and performance benchmarks if disclosed. Prioritize managers that have not yet had a first close so we can negotiate better LP terms.
4. The Head of IR Candidate Slate for a Growth-Stage Hedge Fund
For: Managing partners at asset management executive search firms building a candidate slate for a hedge fund formalizing its IR function for the first time The Job: Identifying IR and capital formation professionals at AUM-qualified hedge funds with institutional pedigree, international LP experience, and tenure signaling openness to a move
The prompt
Using Dakota Marketplace's contact and career history data, identify professionals currently in Head of Investor Relations, Director of IR, or VP of Capital Formation roles at hedge funds or alternative asset managers with $500M–$5B in AUM. Filter for candidates who have: (1) been in their current role for 3+ years, suggesting proven capability and potential openness to a new opportunity; (2) prior experience at a larger institution such as a top-25 hedge fund, major prime broker, or bulge bracket bank; and (3) a track record spanning both domestic and international LP development. For each candidate, provide: name, current employer, title, approximate tenure in current role, educational background, direct contact info if available, and any notable LP relationships in their career history. I'm building a slate for a $2B hedge fund client who is formalizing their IR function for the first time.
5. The High-Growth RIA Compliance & Data Platform Prospect List
For: Heads of enterprise sales at alternative investment data and compliance platforms targeting fast-scaling RIAs The Job: Building an outbound target list of post-2015 RIAs growing rapidly in AUM with lean teams most in need of scalable compliance and reporting infrastructure
The prompt
Using Dakota Marketplace, identify registered investment advisers that: (1) have AUM between $500M and $5B (high-growth, scaling firms), (2) AUM has grown by more than 25% in the last reported period, (3) firm was founded or registered after 2015 (more likely to be on modern infrastructure), (4) have between 5 and 50 employees (lean teams most in need of automation), (5) are based in the US. For each result, show: firm name, AUM, AUM growth rate, registration date, headcount, city and state, Chief Compliance Officer name and email, CEO/Founder name and email, and any known technology partners or CRM systems in use. Sort by AUM growth rate descending — fastest-growing firms have the most urgent need for scalable compliance and reporting tooling.
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.
