Data sourced from Dakota Marketplace, the global LP and GP intelligence platform trusted by thousands of investment professionals. 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 RIA Compliance Infrastructure Upgrade Prospect List
For: Account Executives at compliance and cybersecurity software companies targeting registered investment advisers and alternative managers outgrowing legacy infrastructure. The Job: Identifying RIAs and alternative asset managers with rapid AUM growth or significant headcount additions in the last 18 months — the clearest signals of compliance software upgrade need — with CCO and COO contacts ready to load into CRM.
The prompt
I sell compliance and cybersecurity software to registered investment advisers and need a targeted prospect list. Using Dakota Marketplace, identify RIAs and alternative asset managers between $500M and $5B in AUM that have grown AUM by more than 30% or added ten or more employees in the last 18 months, based on Form ADV filing history. For each firm, show current AUM, AUM growth, headcount added, and the CCO or COO contact who would own a compliance software decision. Return a prioritized outreach list I can load into our CRM this week.
2. The Take-Private Co-Investor Target List
For: Directors of Financial Sponsors Coverage at middle-market investment banks helping PE sponsor clients fill co-investment gaps in take-private transactions. The Job: Identifying family offices and endowments with active direct co-investment programs and documented industrials or business services co-investment history, ranked by check-size fit and speed-to-close likelihood.
The prompt
I'm advising a PE sponsor on a $400M take-private transaction and need to help them fill a $75M co-investment gap. Using Dakota Marketplace, identify family offices and endowments with $1B or more in AUM that have documented direct co-investment programs and have made at least one co-investment in the industrials or business services sector in the past three years. For each, show AUM, typical check size if known, key decision-maker contact with title and email, most recent co-investment activity, and any existing relationship with our sponsor client's other funds. Rank by check-size fit and speed-to-close likelihood. Return a ranked target list I can share with the deal team this week.
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 Head of Distribution Candidate Longlist for a Multi-Strategy Hedge Fund
For: Partners at financial services executive search firms running retained Head of Distribution searches at multi-strategy hedge funds diversifying their allocator channel mix. The Job: Identifying distribution leaders at competing hedge funds with documented multi-channel coverage spanning public pension, RIA, and family office relationships, flagged by tenure in the sweet spot for a move.
The prompt
I'm retained to find a Head of Distribution for a $6B multi-strategy hedge fund that needs to diversify beyond its current institutional base into RIAs and family offices. Using Dakota Marketplace's career history and contact data, identify sales and distribution leaders at competing multi-strategy or macro hedge funds who have documented relationships spanning at least three allocator channels — such as public pension, RIA, and family office. For each candidate, show current firm and title, years in current role, firm AUM, the channels they are known to cover based on Dakota contact and relationship data, and any prior firms. Flag candidates who have been in their current seat for three to six years. Return a ranked longlist of 25 candidates as a PDF I can present at the client kickoff.
4. The External Manager Portfolio Monitoring Briefing
For: Deputy CIOs at corporate pension plans monitoring existing external managers for new fund launches, strategy expansions, and elevated risk signals ahead of re-up and diversification decisions. The Job: Pulling a structured briefing of all external managers with new fund launches, Form ADV amendments, or leadership changes in the last 12 months, organized by manager for investment committee review.
The prompt
Using Dakota Marketplace, pull a list of all external managers currently in our portfolio and identify which of them have launched a new fund, added a new strategy, or filed a new Form ADV amendment in the last 12 months. For each manager with a new offering, show the new fund or strategy name, target AUM or fund size, asset class, and how it differs from what we currently hold with them. Also flag any managers where recent SEC filings or leadership changes suggest elevated risk — such as key-person departures or declining reported AUM. Return a briefing PDF organized by manager that I can bring to our next investment committee meeting to evaluate re-up and diversification opportunities.
5. The Emerging Private Credit Manager First-Close Tearsheet Pack
For: Heads of Fundraising at emerging manager private credit funds building a targeted allocator tearsheet pack for a first institutional close. The Job: Profiling six endowments, foundations, and public pensions with documented emerging manager commitment history in private credit, paired with relationship warmth notes and consultant gatekeeper context for each.
The prompt
Build me a tearsheet of 6 allocators — a mix of endowments, foundations, and public pensions — that have a documented history of committing to emerging or first-time private credit managers with checks between $10M and $25M. Include AUM, current private credit allocation percentage, most recent commitment to an emerging manager, and the two best contacts for our capital raise, with notes on relationship warmth and any consultant gatekeeper.
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.
