We’ve entered a new era.
When you connect a complete, accurate, enriched, and daily-updated private markets dataset directly to your existing workflow through Claude, you can do things that simply weren’t possible before.
Not harder. Not slower. Not possible.
A filter-based database returns records. AI connected to the right dataset returns answers, analysis, and deliverables. For private equity deal teams, that distinction changes the nature of the work itself.
The Dakota Marketplace connector for the Claude app puts nearly thirty years of practitioner-built LP, GP, fund, portfolio company, and transaction data inside the same conversation where you already draft memos, prep for meetings, and think through deals.
Below are the ten use cases I believe will define how PE professionals work once that connector is live — workflows no amount of logging in, filtering, and exporting could ever replicate.
Top 10 Things PE Deal Teams Can Do With Dakota Marketplace in the Claude App
1. One-shot screening and IC memos
“Draft a preliminary screen on Target Co.” In one pass, you get the company profile, sponsor history if PE-backed, comparable transactions, management background, and a competitive set — assembled into the memo format your firm actually uses. In Marketplace, you’d open eight tabs and rebuild that document by hand every time. In the Claude app, the first draft writes itself before you finish your coffee.
2. Compound natural-language sourcing
“Founder-owned industrial distribution businesses, $5–15M EBITDA, in Texas or Oklahoma, where the founder is over sixty and there’s no prior institutional capital.” That’s a filter combination that either doesn’t exist in any UI or takes twenty minutes to construct. In chat, it takes three seconds. The interface is your sourcing thesis itself.
3. Bolt-on and add-on target lists for portfolio companies
“For our HVAC services platform, give me a ranked bolt-on list with strategic rationale for each.” Dakota supplies the universe of qualifying targets. Claude reasons about strategic fit, geographic adjacency, and likely seller motivation. The web app can return a list. It can’t tell you why each name belongs on it.
4. Competitor sponsor intelligence briefings
“Brief me on what [Competitor PE Firm] has done in healthcare services over the last twenty-four months — new platforms, add-ons, exits, average hold periods, and disclosed multiples where available.” You receive a synthesized narrative, not a search result. The kind of intelligence that used to require a junior analyst and half a day now arrives in a single response.
5. Pre-meeting prep across Dakota, Gmail, and Calendar
“I’m meeting [Banker] tomorrow at ten — pull our email history with him, the recent deals he’s run, and any portfolio overlap with his current mandates.” This is the workflow that only exists in the Claude app. Dakota Marketplace gives you the market data. Your own connected tools give you the relationship context. Claude weaves them into a one-page brief that walks into the meeting with you.
Stop logging in. Start asking. The Claude App connects Dakota Marketplace's full private markets dataset to the conversation where deal teams already work — included with every subscription.
6. Precedent transactions with iterative synthesis
“Build a precedent transactions table for vertical SaaS deals in HR tech, $50–200M enterprise value, over the last five years.” Then: “Now write the valuation-trend paragraph for the IC memo.” Then: “Filter out the ones with strategic buyers and recompute the median multiple.” This is iterative refinement that filter-based interfaces fundamentally cannot do. You’re not searching the dataset. You’re thinking out loud against it.
7. Management team backgrounding
“Tell me about this CEO — prior PE backing, board seats, exits he’s led, and the operators he’s typically worked with.” Dakota’s contact and transaction history combined with public sources produces the kind of one-page executive profile that used to be a paid service. Now it’s a question.
8. Strategic buyer and exit universe mapping
“Build the likely strategic acquirer universe for our portfolio company.” You get a ranked list of corporates and sponsors actively acquiring in the space, recent transaction sizes, strategic rationale for each, and the prior bankers involved. This is exit planning as a deliverable, not a research project.
9. LP and co-investor identification with relationship context
“Find me LPs who back lower-middle-market industrials specialists writing $20–50M tickets, and flag the ones we already have a relationship with.” Dakota’s commitment data crossed with your own CRM and inbox. The web app can show you the universe of LPs. Only Claude can tell you which of them already know your name.
10. Pattern recognition across the dataset
“Has PE activity in convenience store roll-ups accelerated in the last six months? Show me the trend and the most active sponsors.” Analytical questions that require querying, reasoning, and visualization in a single motion. You’re not pulling a report — you’re having a research conversation with the entire private markets dataset at once.
The Thread Through All Ten
Deal teams don’t want records. They want answers and deliverables.
Dakota Marketplace remains the source of truth — practitioner-built, daily-refreshed, and the most complete private markets dataset available anywhere. The Claude app is where that truth becomes work product.
That’s the new era. The engine is AI. The fuel is data. And once you’ve connected the two, the workflows start to look nothing like they used to.
The engine and the fuel are ready, see the Claude App for Dakota Marketplace and connect the two for your team.
