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Investor profile

Daniel Gross

Angel investor · San Francisco, USA · Founded 2018 · 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

16 Power Law outcomes Power Law Ranking #97 · 16 Power Law outcomes · Active 2026
Enterprise value ↑ 176% 5y
$186B
Unicorns ↑ 60% 5y
16
Decacorns ↑ 250% 5y
7
Thoroughbreds ↑ 60% 5y
16
Featured in #97Power Law Investor Ranking · Global · 2026 Top 1%by Seed → $100M+ revenue outcomes

Daniel Gross is an angel investor based in San Francisco, USA, founded in 2018. The page below shows 16 Power Law outcomes from Daniel Gross's portfolio — 16 unicorns ($1B+ valuation) and 0 additional thoroughbreds (companies that crossed $100M+ in revenue without yet reaching $1B+ valuation).

Outcomes are concentrated in AI · Fintech · Transportation; top portfolio geographies are USA · Decentralised · UK. Daniel Gross ranks #97 globally in the 2026 Dealroom Power Law Ranking by Seed → $100M+ revenue companies.

Portfolio analysis

The 16 Daniel Gross Power Law outcomes ($100M+ revenue and above).

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

By countryCount
  1. USA14
  2. Decentralised1
  3. UK1
By sectorCount
  1. AI9
  2. Fintech2
  3. Transportation2
  4. Robotics1
  5. Biotech & Life Sciences1
  6. Other B2B Software1
By stage enteredCount
  1. Series B+5
  2. Series A5
  3. Seed6
01 · Portfolio market map

Daniel Gross's 16 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
16 of 16 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 Daniel Gross first invested in (where data is available — coverage 93%).
02 · Origin of portfolio founders

Where Daniel Gross's founders come from — and where they study.

37 founders across the 16 Power Law outcomes — split by country of origin, university attended, and the company they worked at before founding. Stanford University and Alphabet | Google are the deepest single pipelines.

LocationCount
United States21
Canada3
India3
Poland3
Belarus1
View on app →
UniversityCount
Stanford University4
University of Waterloo3
New York University3
Berkeley3
Duke University2
University of Illinois Urbana Champaign2
Massachusetts Institute of Technology2
Indian Institute of Technology, Madras1
University of Cambridge1
Imperial College London1
+9 more →
Origin companyCount
Alphabet | Google4
Yahoo!2
Twitch2
Quora2
Meta2
Cvent1
Jama Software1
Groupon1
Cruise1
Tesla1
+16 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 Daniel Gross.

Senior investment team at Daniel Gross 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 Daniel Gross stack up?

Daniel Gross 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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