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Investor profile

Garry Tan

Angel investor · San Francisco, USA · Founded 2010 · Active in 2026

← Power Law Ranking

A public taster of the full Dealroom platform — request a demo to explore live deal flow, full investor history, and team intel. · Last updated 15 Apr 2026 · Methodology

10 Power Law outcomes Power Law Ranking #53 · 10 Power Law outcomes · Active 2026
Enterprise value ↓ 7% 5y
$87B
Unicorns ↑ 125% 5y
9
Decacorns ↓ 50% 5y
1
Thoroughbreds ↑ 150% 5y
10
Featured in #53Power Law Investor Ranking · Global · 2026 Top 1%by Seed → $100M+ revenue outcomes

Garry Tan is an angel investor based in San Francisco, USA, founded in 2010. The page below shows 10 Power Law outcomes from Garry Tan's portfolio — 9 unicorns ($1B+ valuation) and 1 additional thoroughbreds (companies that crossed $100M+ in revenue without yet reaching $1B+ valuation).

Outcomes are concentrated in Fintech · Other B2B Software · AI; top portfolio geographies are USA · Germany. Garry Tan ranks #53 globally in the 2026 Dealroom Power Law Ranking by Seed → $100M+ revenue companies.

Portfolio analysis

The 10 Garry Tan Power Law outcomes ($100M+ revenue and above).

Snapshot of where the outcomes are concentrated by country, sector, and stage entered.

By countryCount
  1. USA9
  2. Germany1
By sectorCount
  1. Fintech2
  2. Other B2B Software2
  3. AI2
  4. eCommerce & Marketplaces2
  5. Marketing1
  6. Biotech & Life Sciences1
By stage enteredCount
  1. Series B+1
  2. Series A2
  3. Seed7
01 · Portfolio market map

Garry Tan's 10 Power Law outcomes.

Toggle between a sector landscape and a world map. Both views respond to the stage and outcome-tier filters. The faded names at the bottom of bigger boxes are part of the full list — click "+ N more" to reveal them.

Stage entered
Outcome tier
Region
Group by
10 of 10 Power Law outcomes
Logos hosted by Dealroom; click any chip to open the company in app.dealroom.co. The dot inside each chip shows the company's highest tier — red Gigacorn, violet Centicorn/Decacorn, lavender Unicorn, blue Thoroughbred, green Colt. Tiers are inclusive: a Unicorn (e.g. Klarna) also matches the Thoroughbred filter, a Decacorn also matches Unicorn and Thoroughbred, and so on up the ladder. Colt is a separate axis (high-growth, smaller revenue) and only matches itself. Map dots use the same colour code; hover for details. Sectors are mutually exclusive (priority-ordered classification). Stage entered = the round Garry Tan first invested in (where data is available — coverage 93%).
02 · Origin of portfolio founders

Where Garry Tan's founders come from — and where they study.

37 founders across the 10 Power Law outcomes — split by country of origin, university attended, and the company they worked at before founding. Stanford University and Stability AI are the deepest single pipelines.

LocationCount
United States14
Germany10
Brazil1
Romania1
View on app →
UniversityCount
Stanford University9
Duke University3
Washington University in St. Louis2
University of Michigan2
University of Michigan Ross School of Business2
Carleton University1
University of Bordeaux1
University of Tübingen1
University of Heidelberg1
Ludwig Maximilian University of Munich1
+7 more →
Origin companyCount
Stability AI4
Microsoft3
Alphabet | Google3
Digital Turbine2
X.2
Sift1
Nvidia1
Zillow1
Mozilla1
Yelp1
+10 more →
Origin = country a founder is born in or grew up in (founders may have multiple origins; counts include all entries). University = highest-listed degree. Origin company = a previous employer where the founder was tagged before starting their current company. Explore the full Sequoia infographic on Thoroughbreds & Unicorns →
03 · Key people

Key people at Garry Tan.

Senior investment team at Garry Tan has not been published on this profile yet.
Suggest the partner roster →
No partner roster has been published on this profile yet.
04 · Compare with peers

How does Garry Tan stack up?

Garry Tan in orange, your selection in blue and other colours. Pick from the global roster of 35 peer investors — filter by region or hit "Find similar shapes" to auto-pick the three closest. The funnel matrix mirrors the spider chart on the ranking page; the line chart shows each firm's share of global unicorns minted that year — peaks reveal vintage years.

Compare against

Stage focus

Companies by entry stage and outcome tier

Sector focus

Companies per investor across the 10 highest-volume sectors

Share of new unicorns per year

% of all global unicorns minted that year, year by year
Source: Dealroom Power Law dataset. Investors shown are the 2026 Power Law top 35 by combined entry-to-outcome score, drawn from the overview and locations_data sheets. Funnel-matrix axes rescale per-axis using the maximum among the currently selected investors, so the polygons always fill the chart for shape comparison.

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Data as of 15 Apr 2026 · Source: Dealroom Power Law dataset · Methodology
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