How Joe Works

Inside the platform behind the reference line.

Search fund performance, GP & sponsor intelligence, and private company transactions in one place, then benchmark and export what you need. Here's what's actually inside Joe.

Three steps from question to answer.

No stitching together spreadsheets from three vendors. Search the full dataset, narrow to a real peer set, and export what you need.

1
 

Search & filter

Narrow 18,000+ funds by asset class, sub-strategy, vintage year, geography, and fund size in a few clicks.

2
 

Compare against peers

See Net IRR, TVPI, DPI, and RVPI side by side against the vintage-matched peer group, not a broad average.

3
 

Export & report

Pull the exact cut you need into Excel or CSV for an investment committee memo or diligence file.

A search screen built for peer comparison.

Illustrative interface, filters on the left, ranked results on the right, every fund tagged the same way.

 
 
 
joe.dakota.com/search
Funds
Sponsors
Companies
Transactions
Asset Class
 Private Equity
 Private Real Estate
 Private Credit
 Venture Capital
Sub-Strategy
 Buyout
 Growth Equity
Vintage Year
 2018 – 2020
Geography
 North America
214 funds match your filters Export CSV
Fund Vintage Net IRR TVPI DPI
Fund XII, L.P. 2019 18.4% 1.6x 0.9x
Joe Growth Partners IV 2018 15.1% 1.5x 0.8x
Cornerstone Buyout Fund VI 2020 21.7% 1.7x 0.6x
Frontier Capital Partners V 2019 12.9% 1.4x 1.0x
Ridgeline Equity Fund III 2018 17.3% 1.6x 0.7x

What's inside.

 

Search & filter

Filter funds, sponsors, companies, and transactions by asset class, sub-strategy, vintage year, geography, and fund size.

 

Standardized fund metrics

Net IRR, TVPI, DPI, and RVPI captured consistently at the fund level for every record.

 

GP & sponsor intelligence

Investment theses, portfolio companies, deal activity, and team intelligence for every tracked sponsor.

 

Private company transactions

Deal-level entry multiples, structures, and sector coverage across sponsored and non-sponsored businesses.

 

Custom benchmarking

Build bespoke peer groups by vintage, strategy, geography, fund size, and portfolio company sector.

 

Non-sponsored business data

Proprietary coverage of companies without a PE sponsor, built for proactive origination outreach.

 

Fund & sponsor profile pages

Every fund and sponsor has a dedicated record with full history, not just a summary line.

 

Export to Excel & CSV

Pull filtered results directly into a diligence file, IC memo, or pitch book.

 

Daily data updates

Coverage refreshes continuously rather than on a quarterly reporting lag.

The data gets you in the room. The connection is what closes it.

Standalone performance data is table stakes now, most legacy fund databases can hand you a Net IRR and a TVPI. What most of them can't do is connect that number to who you already know. Joe ties fund and GP performance directly to Dakota's fundraiser-built LP relationship graph and GP & sponsor intelligence, so a benchmark isn't just a number sitting on its own, it sits next to the allocator relationships and firm context you'd otherwise have to go build in a second, disconnected tool.

That same connected dataset is now queryable at inference time through a native Claude connector, so a research or IR team can ask the question directly inside the tools they already work in, instead of opening a fifth login just to look it up.

A single, transparent price and a workflow already wired into your relationship data is what wins the deal, not the data in isolation, and not a quote-based, five-figure-plus enterprise contract.

1
Fund & GP Performance Net IRR, TVPI, DPI, and RVPI standardized across 18,546 funds
2
LP Relationship Graph The same fundraiser-built allocator relationships that power Dakota Marketplace
3
GP & Sponsor Intelligence Investment theses, portfolio companies, and deal activity on every tracked sponsor
4
AI-Native Delivery Query the connected dataset directly through a native Claude connector, no separate login required

Research-verified, not self-reported.

Every record in Joe, fund, sponsor, company, or transaction, is reviewed by a research team before publication. Not auto-populated from a filing, not scraped from a press release, and not taken at face value from a GP's marketing deck.

That verification step is what makes the data usable for diligence, origination, and fundraising conversations alike: everyone can trust the same number without re-checking the source.

See our full methodology →
1
Source Fund, sponsor, and transaction data is gathered from GP reporting, LP disclosures, and public filings.
2
Verify Every record is reviewed by Joe's research team before it's published.
3
Structure Each record is tagged by asset class, sub-strategy, vintage, geography, and sector.
4
Refresh Records are updated continuously rather than on a fixed quarterly cycle.

Built on Dakota's data infrastructure.

Joe runs on the same platform infrastructure that powers Dakota Marketplace for thousands of investment professionals.

 
One login A single Dakota account covers Joe access, no separate credentials to manage.
 
Gated access Request Access routes through a short qualification step, pricing stays visible either way.
 
Up to 5 users Included in the base plan, no per-seat surprise for a small research or IR team.

Common questions.

How is Joe's data sourced and verified? +

Fund performance is gathered from GP reporting, LP disclosures, and public filings, then reviewed by Joe's research team before publication, not auto-populated or taken at face value.

How often is the data updated? +

Continuously, rather than on a fixed quarterly cycle. New fund records and updated metrics are added as they're verified.

Can I export data out of Joe? +

Yes — filtered search results export directly to Excel or CSV for use in a diligence file or investment committee memo.

What's included in the price? +

Full access to Joe — 18,000+ funds across 7 asset classes plus evergreen & interval coverage, GP & sponsor intelligence, private company transactions, non-sponsored business data, and custom benchmarking — for up to 5 users. Request Access to confirm current terms. [Price under review following the recent scope expansion — see internal brief.]

Is there a sample before I request access? +

Yes — see a real fund report on a Dakota Joe demo with one of our team members.

Does Joe include GP intelligence and transaction data, or just fund performance? +

Both. Joe covers fund performance, GP & sponsor intelligence (investment theses, portfolio companies, deal activity), private company transactions (sponsored and non-sponsored), and custom benchmarking — everything previously in Dakota's Private Markets product, now under one login.

How is Joe different from a standalone performance database? +

Most performance databases stop at the fund record. Joe connects that same performance data to Dakota's fundraiser-built LP relationship graph and GP & sponsor intelligence, and makes the whole connected dataset queryable at inference time through a native Claude connector, so it doesn't just answer "what's the number," it sits next to who you already know. That's on top of a single, transparent $9,500/yr price instead of a quote-based, five-figure-plus enterprise contract.

How is Joe different from Dakota Marketplace? +

Joe covers the private markets side: fund performance, GPs, portfolio companies, transactions, and benchmarking. Dakota Marketplace is the LP and allocator side, fundraising research and CRM workflows for reaching institutional and wealth-channel investors. Looking for LPs to raise capital from? That's Dakota Marketplace.

One plan. Full access.

$9,500/yr
Up to 5 users included
  • 18,546 funds across 7 asset classes, plus evergreen & interval coverage
  • Net IRR, TVPI, DPI, and RVPI on every record
  • GP & sponsor intelligence, private company transactions
  • Non-sponsored business data
  • Custom benchmarking, export to Excel & CSV
  • Daily data updates
Request Access

See where a fund actually stands.

Get access to Joe and benchmark private fund performance with data built for the comparison you're actually trying to make.

 

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