2021: the year
of Deep Tech.
8 January 2021
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EuropeanStartups.co
About European Startups.
Created by Dealroom and Sifted, and supported by the European
Commission and European Parliament, European Startups is a
two-year project aimed at facilitating informed conversation and
collaboration among European tech ecosystem stakeholders, to
take Europe’s startup economy to the next level.
At the centre of the initiative is the European Startups database, a
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insights for data-driven policy making, complemented with
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Previous reports
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EuropeanStartups.co
Why this Deep Tech report.
A big thanks to
This report heavily leans on insights from conversations with:
The term Deep Tech invokes great excitement for some, scepticism for
others, and sometimes both simultaneously.
Excitement, because of things like quantum computing, autonomous
vehicles, and protein folding solutions. Artificial Intelligence alone could add
another $13 trillion to the global economy over the next decade, according
to McKinsey. The potential value of nuclear fusion or curing cancer is hard
to overstate.
Meanwhile, there’s also scepticism, not about these innovations, but about
the term “Deep Tech”. Firstly, it’s rather vague. Secondly, it implies a too
narrow focus on cool technologies for their own sake, while losing sight of
commercialisation and competitiveness.
The EU is heavily investing in strengthening Europe’s Deep Tech and
Blockchain ecosystem. But there is a worry that this effort is insufficiently
supported by efforts
to make Europe more competitive and
entrepreneurial.
This report aims to better establish what Deep Tech actually is, how
Europe’s ecosystem works, what it’s lacking, how it can compete and what
desirable policy goals might be.
Dr. Inga Deakin
Principal
Draper Esprit
Nicolas Colin
Co-founder & Director
The Family
Siraj Khaliq
Partner
Atomico
Rodolfo Rosini
CEO
Undead
Gil Dibner
General Partner
Angular Ventures
Suranga Chandratillake
General Partner
Balderton Capital
Nathan Benaich
Founder & General Partner
Air Street Capital
Stephen Nundy
Technology & VC Investor
Lakestar
Julia Hawkins
Partner
LocalGlobe
Page / 4
EuropeanStartups.co
2021: a pivotal year for Deep Tech.
The last decade has created $17 trillion of value on the NASDAQ alone,
mainly driven by enterprise cloud and consumer internet. In the decade
we’re now entering, tech’s impact on our lives might become much more
profound. Major technological breakthroughs have been accumulating at
an accelerated pace.
Just to name a few milestones: In 2019 Google (with NASA) achieved
“quantum supremacy”, only to be topped by China by a factor 10 billion in
2020. The CRISPR-Cas9 genome editing technique was awarded the
Nobel prize in 2020 while Crispr Therapeutics’ market capitalisation
tripled to $11 billion. DeepMind solved a major protein folding challenge
(AlphaFold) while it’s MuZero program marked another milestone in
self-learning AI (MuZero can teach itself to play Go, chess, and Atari
games). OpenAI released GPT-3, a language model that uses deep
learning to produce human-like text. And the list goes on.
So far, this might have seemed abstract to outsiders. However, we are
now witnessing the first ever mRNA-based vaccine in use to combat
Covid-19. SpaceX’s spectacular rocket launches/landings speak to the
imagination. Deep Tech is starting to become much more visible and
impactful to a wider audience. We can expect more breakthroughs in
2021, dominating several headlines, becoming much more tangible, and
directly solving global social and business challenges.
Tech is entering a new era.
Personal
computing
The
Web
Mobile
computing
Cloud
computing
Deep
Tech
1980s
1990s
2000s
2010s
2020s
“Software eating the world”
$17 trillion value created on NASDAQ
alone
NASDAQ Composite

Development of mRNA
platform that will later be
used to develop the
Covid-19 vaccine.
Covid-19 vaccine Tozinameran
becomes the first widely
authorized Covid-19 vaccine.
The success of BioNTech demonstrates the importance of long-term R&D, but also
the role of government and the need for stronger European capital markets.
Page / 5
BioNTech is founded as a spinout from
Mainz University. Its focus is on
individualized cancer medicine:
tailor-made immunotherapy for each
individual patient based on the genetic
features of the tumor.
2008
Jan 2018
€225M
Series A
Oct 2019
IPO on
NASDAQ
$3.4B
value
Jan
2020
Today, BioNTech is valued at $22
billion. Tozinameran is the
world’s first mRNA vaccine in use.
Expectations are high for mRNA
platforms of BioNTech and its
peers. Potential mRNA
applications range from cancer
treatments to malaria and AIDS.
Received €9.4 million in EU funding since 2009
Project “lightspeed” started to
develop Covid-19 vaccine
(announced in March 2020).
Now
$425 million partnership with
Pfizer to develop mRNA
vaccines for influenza (flu).
Source: Dealroom.co.
BioNTech received over $1.3 billion
in funding, from both European, US
and Asian investors. In the end it
chose a US listing.
See full company profile
€5.0B valuation
Semiconductors
€1.8B valuation
Semiconductors
* NXP was close to being acquired by Qualcomm.
** ARM is about to be acquired by Nvidia.
Page / 6
€9.3B valuation
Robotic process
automation
€9.5B valuation
DNA sequencing
€3.4B valuation
Biotechnology
€20B valuation
Biotech
€3.0B valuation
Automotive
€2.3B valuation
Robotic process
automation
€2.0B valuation
Semiconductors
€1.8B valuation
Game development
platform
€1B valuation
Flying vehicles
€1B valuation
Biotech
€1B valuation
Minimally invasive
surgery robots
€1.8B valuation
Robotic process
automation
€1.8B valuation
Semiconductors
€1B valuation
Neuroscience and
digital therapeutics
€1.8B valuation
Health platform
€45B valuation *
Semiconductors
€162B valuation
Semiconductors
€44B valuation **
Semiconductors
€46B valuation
Medical devices
€44B valuation
Medical devices
€34B valuation
Telecommunications
€18B valuation
Telecom
€28B valuation
Semiconductors
€28B valuation
Geospatial apps
€42.3B valuation
Semiconductors
Notable Deep Tech companies founded since 2000
Notable Deep Tech companies founded before 2000
€5B
€39B
€188B
2010
2015
2020
Combined value of European-
founded Deep Tech companies is
nearly €700 billion and growing
€183B
€229B
€508B
2010
2015
2020
€1.5B valuation
Enterprise
cybersecurity
Page / 7
The next decade requires
bottom-up streamlining and
top-down strategic thinking.
Successes like BioNTech demonstrate the
importance
of
early
support
from
governments
and universities.
Such
programs need to be streamlined to really
attract Europe’s top talent (bottom-up).
Meanwhile, Europe could benefit from
replicating some of the
large scale
long-term strategic R&D approaches of
the US (DARPA) and China, to ensure tech
leadership (outside academia) in areas
which are going to become important in
2035+. As Marc Andreessen wrote, “It’s
time to build.”
Some of the most successful startups will
manage to break through silos, by
combining disciplines, while attracting
different talent and
investors across
stages of development.
Universities,
governments,
specialised
deep tech investors and agnostic venture
capital
investors should move closer
towards each other
to help such
companies succeed and scale.
Closer collaboration needed
to support Europe’s most
promising Deep Tech startups.
Europe’s Deep Tech companies are worth
a combined €700 billion today. Many have
their roots in academia and drew early
support from government grants.
Yet there’s a lot more potential to be
unlocked.
Europe’s
universities
and
research really are world-class. The
commercial gap with China and the US can
be closed by fostering an entrepreneurial
culture on campuses, training first-time
academic entrepreneurs and tech transfer
officers, and offering spinouts simpler and
faster deals.
There’s unlocked potential in
Europe’s leading academic
institutions.

What is Deep Tech?
Europe’s Deep Tech investment landscape
Competing globally in the age of Deep Tech
From Deep Tech to Deep Purpose
1 What is Deep Tech?
EuropeanStartups.co
Page / 10
What is Deep Tech?
"For a startup to earn the "deep tech"
label, there must be science or
engineering risk in getting the idea to
actually work and, assuming it does,
risk in proving market demand for
that product. If there is only one of
these risks, but not both, then we're
not talking about a "deep tech"
startup.”
Nathan Benaich
Founder & General Partner
Biotech
Deep tech:
Higher R&D risk,
product-market risk
Startup copying other
successful startup
(Cazoo, Zalando) *
Innovating startup
Product-market risk
(risk of not finding fit)
R&D risk
(risk of R&D not
succeeding)
*Cazoo is a perfect example of a startup with all major risks mitigated: serial founder,
proven business model and technology (of course many risks remain).
Deep Tech combines multiple risks at once
(inspired by Nicolas Colin).

Biotech startup
Long and costly testing phases
Discovery phase becoming shorter *
Less market risk **
R&D
Investment
Acquisition / JV
R&D
Go-to-market
Growth
Seed
Early
Late
Regular startup
Exploit new but proven technologies
Validate product-market fit as early as possible
R&D and patent ownership is rare
Page / 11
Deep Tech (and Biotech) startups have a longer cashburn. But advancements in AI, and
more experienced talent pools could bring them more in line with regular startups.
Discovery
phase
Searching for
product-market fit
Over 70% don’t
graduate from seed
to series A
Testing
phases
Extended R&D phase
Regulatory
approval
Value
Value
Value
Deep tech startup
Starts with extended R&D phase
Higher share of technical staff
Often involves hardware and/or IP
* AI, mRNA, digital therapeutics and gene editing make biotech gradually more like tech startups, at least for discovery phase.
** There’s generally a market for curing diseases. But it has long been difficult to get funding for flu vaccines, for instance.
€150B / year
Corporates
Amount is the annual European
corporate R&D spend (nearly half by
pharma and automotive)
Rationale
✔ Enable growth (e.g. Facebook and
Google investing in rural internet) and
secure future (e.g. investing in quantum
computing) *
Breeding ground
Academia
Many deep tech companies arise from
universities. Some as spinouts: startups
where universities have equity and/or
royalty/licensing deals. Others as
independent startups
Rationale
✔ Make an impact
✔ Potential to create a spinout
✔ Universities: attract funding
Page / 12
~€12B / year
Government
Horizon Europe: €100B / 7 years
National innovation programs =
hundreds of millions per country
(Bpifrance is >€1B/year, Innovate UK ~
£1B/year)
Rationale
✔ Technological sovereignty/autonomy
✔ Tackling global challenges (climate,
curing disease, access to healthcare,
food)
€10B / year
Venture capital
Roughly a quarter of VC invested in
Europe goes to Deep Tech startups
Rationale
✔ Capture new market opportunities
✔ Backing early-stage tech to find
breakthroughs to progress ecosystem
Greater risk, but also greater support from multiple directions.
* As Nicolas Colin writes: while “software is “eating the world”, Deep Tech is needed to “digest” the world.
Company
Category
University
Grants
VC funding
Biotech
Mainz
European H2020 programs
€1.3b
Identity verification
Oxford
Eurostars SME Programme, Tech Nation
€192m
Light-emitting diodes
CEA
European Innovation Council (EIC)
€171m
Satellites
Aalto
European Commission, Eurostars SME Programme
€123m
Carbon sequestration
ETH Zurich
Eurostars SME Programme
€114m
Edge AI chips
Bristol
EIC
€102m
AI-based drug discovery
Dundee
Bill & Melinda Gates Foundation
€96m
Quantum computing
Aalto
EIC
€68m
Intralogistics robots
TUM
EXIST
€41m
Intelligent microprocessors
CEA
Eurostars SME Programme
€34m
Autonomous vehicle software
Oxford
Innovate UK
€70m
Professional drones
ETH Zurich
EIC
€27mp
AI-based diagnostics
Oxford
Government of the UK, NIHR
€24m
Graphene-based electronics
Cambridge
ERDF
€23m
Plastic recycling
Warwick
EIC, UKRI
€20m
Quantum computing
Cambridge
Government of the UK
€4m
Biotech (Oxford’s Covid vaccine)
Oxford
UKRI
€43m
Super resolution microscopes
Oxford
n/a
€27m
Page / 13
EuropeanStartups.co
Many of Europe's top Deep
Tech companies have their
roots in academia and drew
early support from
government grants.
Gil Dibner
Founder, Angular Ventures
“The private markets are efficient at identifying
and funding companies that have commercially
viable technology. The best use of public
money is to fund scientific and academic
research in the absence of a commercially
viable business case. That is where there is a
market failure that governments can correct.
Over the long run, that sort of research tends
to have tremendously positive knock-on
effects for society and the economy – often
for decades.”

Prototyping
True environment testing
Commercial demos
Go to market
Production
In operation
Recruit new skills
Experiments
Concept generation
Analytical proof
Lab testing
Source: Dealroom.co based on discussion with Stephen Nundy from Lakestar and others. Stages based on Technology Readiness Levels used by governments.
Page / 14
Growth phase
Commercialise
Recruit new skills
Scale tech
Closer collaboration between European
generalist VCs and Deep Tech investors
would be desirable.
University
research faculty
Tech Transfer
Offices
Deep Tech investors
(MIG, OpenOcean, Air Street, ...)
Generalist VC funds
(Lakestar, Atomico, LocalGlobe,
Balderton, Index, ...)
Government funding
(Horizon2020, Innovate UK, Bpifrance, …)
Corporate sponsors
(e.g. pharma, industry, semiconductors)
As ecosystem accumulates experience
and critical mass, R&D phase can accelerate
… and each stakeholder plays a role in taking different types of risks throughout the
lifecycle of a Deep Tech company.
Early support from universities and governments is effectively de-risking
later stage investors in Deep Tech.
“We need to ensure that when deep tech companies go global, their home geography and
ethical values are represented both on the cap table and in the boardroom. Meanwhile,
the private-public financing relationship is one that needs to continue to be nurtured.
There’s been some great progress with EU government grants like Horizon 2020.
Governments can invest alongside private investing “know-how” to ensure they are
leveraging VC expertise and partnership whilst managing risk against the public purse.”
Stephen Nundy
Partner, Lakestar
Deep Tech Investor
“At the moment, deep tech VCs and sector-agnostic VCs are
working in silos. These two investing groups need to move
towards each other to help companies succeed and scale.
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EuropeanStartups.co
Deep Tech is really about what
companies do, rather than
what they are.
Started as consumer internet, now doing Deep Tech
✔
✔
✔
✘
✘
Improbable, in its early days, had to solve hard technical
problems around distributed computing. It has since matured
into a games software infrastructure company and studio.
Darktrace developed foundational unsupervised learning
methods for network security in their early days. Once they
proved success and ROI with early customers, they earned
trust, built their brand equity and could scale from then on.
UiPath
is a global market leader in Robotic Process
Automation (RPA*) and a European flagship example of
successfully commercialized enterprise automation. Today,
the ROI appears so significant that enterprise chase RPA.
✔
✔
✔
?
?
?
Started as Deep Tech, now doing Enterprise SaaS
?
* RPA (Robotic Process Automation), as defined by UiPath: technology that allows anyone today to
configure computer software, or a “robot” to emulate and integrate the actions of a human
interacting within digital systems to execute a business process.
Page / 17
EuropeanStartups.co
It takes (a bit) more
time and capital to build
a Deep Tech startup.
2
years
3
4
5
6
7
8
years
5
10
15
20
25
30
35
40
45
Time between rounds and amounts raised
▊ Deep tech ▊ Tech startups ▊ Biotech
5
3
2
2
2
4
3
4
5
Deep tech
Tech
Biotech
Round 2 means the round after
seed round (considered first)
For tech startups, the first
follow-on round over €4m
happens 1.5 years after seed
round but 2 years for Deep
Tech startups.
We looked at 1,700 qualified European
startups that raised a seed round >€200K
between 2010 and 2015 and closed a 2nd
round of at least €4 million. The approach
taken is based on the methodology from the
Journey to Series A research.
This methodology is very restrictive (many
startups are excluded as their 2nd round
didn’t reach €4 million) but results in a
high-quality, clean data set. The results on a
less restrictive data set are available upon
request.
5
4
3
Page / 18
2nd
round
3rd
round
4th
round
5th
round
10%
20%
30%
40%
Round after Seed round (which is considered 1st round)
Graduation rates between rounds
▊ Deep tech ▊ Tech startups ▊ Biotech
EuropeanStartups.co
Graduation rates of
Deep Tech startups are
higher initially, but then
fall in line with the
broader market.
6th
round
The same 1,700 qualified European startups
were analysed to compare graduation rates
- what percentage of startups with a seed
round successfully raise a next round. Again
here, the first round after seed is at least €4
million.
Across Europe, 24% of startups with a seed
round, make it to the next round. For deep
tech this is nearly 32%.
The pattern could be explained by the fact
that Deep Tech startups need more rounds
before they can be validated.
Deep Tech 32%
Tech 24%
Biotech 40%
15%
12%
13%
6%
6%
3%
2.4%
2.5%
0.9%
Deep Tech companies have the same or even higher probability to
exit. New technology is an attractive bolt-on acquisition for
companies with existing large datasets or virtually unlimited capital
to incur losses. There have been several notable exits. *
Some of these exits may have been painful to watch. And yet, the
temptation to block them is probably best resisted. It would
discourage entrepreneurs (and VCs). Europe should be the continent
to attract the next Elon Musk or Özlem Türeci. Better to address the
root causes of “premature exits” such as lack of late stage growth
capital.
Oxford spinout
Detection of cancer
at an early stage
Acquired by Exact
Sciences for $410m
in Oct 2020
Oxford spinout
Novel AI for game
development
Acquired by Zynga
for $527m
in Jan 2014
World-renowned AI
research laboratory
Acquired by Google
for £400m
in Jan 2014
Machine
Learning-based
visual processing
Acquired by Twitter
for $150m
in Jun 2016
Page / 19
Cumulative % of startups that exit (by round)
▊ Deep tech ▊ Tech ▊ Biotech
Deep tech startups have a similar
probability to exit.
15%
17% 17%
Biotech
Tech
9%
3rd
2nd
4th
5th
3rd
2nd
4th
5th
3rd
2nd
4th
5th
Deep Tech
13%
14%
15%
11%
11%
13%
15%
6%
5%
10%
15%
20%
* For more Deep Tech exits check the Data Platform.
So far, a smaller proportion of Deep Tech startups have reached $1 billion+
valuations. But it’s also a younger ecosystem.
21 companies reached $1B+ valuation (view all)
5 companies reached $1B+ valuation
Cohort of seed rounds
from 2010–2015
(note: there are more Deep Tech unicorns but from different cohorts)
EuropeanStartups.co
Page / 20
Companies from cohort that
surpassed $1B+ valuation
“Yes, they are different disciplines requiring specialisation, but it makes sense to start
collaborating much more across them. The differences that are there will only become
smaller (e.g. AI accelerating drug development, and digital therapeutics). Some of the
most successful startups will manage to break through these silos both in terms of their
ability to attract world class talent from bio as well as tech backgrounds; in addition to
attracting life science as well as tech investors. Especially as these startups will have
different needs across different stages. ”
Julia Hawkins
Partner, LocalGlobe
Health Tech investor
“I think there is a misconception that Deep Tech and Biotech
must have dramatically different risk profiles from tech startups.

2 European Deep Tech investment
landscape.
Venture capital investment in European Deep Tech
companies

€0.7b €1.0b
€1.2b
€1.9b €1.9b
€3.2b
€3.5b
€5.3b
€7.0b
€9.6b €9.4b
10%
16% 16% 17% 16%
20% 20%
24%
26% 25%
24%

With €10B annual investment, Deep Tech
is a quarter of European venture capital.
Notable Deep Tech investors by capital deployed in Europe (random order).
EuropeanStartups.co
Page / 23
% of European VC investment
going to Deep Tech
PsiQuantum (US), Lilium,
Graphcore,
Varjo, Arculus
Isar Aerospace, FiveAI,
Auterion, Eigen
Technologies, Soul
Machines (US), Terra
Quantum
UiPath, Graphcore,
Movidius, ICEYE,
Ledger, Endomag
Darktrace, Sophia Genetics,
Infarm, Healx, Tessian,
ComplyAdvantage, Cleo,
Rahko, The Curious AI
Company, Furhat Robotics
BioNTech, BenevolentAI,
Improbable, SenseTime
(China), Magic Leap (US)
Varjo, Cleo, Cytora,
Wandelbots, Einide,
Riskmethods
Improbable, Tessian, Cleo,
Streetbees, Signal AI,
Faculty
Collibra, Comply Advantage,
Aurora (US), Scale (US),
Behavox (US), Kayrros
Kineis, Carmat, Aledia,
Bioserenity, Owkin, Balyo
Improbable, Graphcore,
Healx, Five AI, XMOS,
Paragraf
Sophia Genetics, Onfido,
Bioserenity, Kaia Health,
WeRide.ai (China)
Improbable, Energy Vault,
Roivant Sciences (US),
Cruise (US), Nuro (US),
View (US)
Quantum Motion, Altitude
Angel, WaveOptics, Ori
Biotech, Phoelex,
AudioTelligence, Swiftkey,
Rangespan, Evi, Magic
Pony, UltraSoC, Zynstra

Northvolt, Graphcore,
Lilium, Aurora (US)
AImotive, CybelAngel,
Intrinsic ID, Ipdia
Isar Aerospace, Vaha,
Verbit (US)
“My own experience, first in raising capital as founder of a deep-tech startup, and
now as an investor who speaks to other founders and investors, is that,
unfortunately, contrarian money is relatively rare. Most investors find it hard to
back businesses with product-market fit risk, yet that is what deep tech entails.
This failure of imagination is costly: by not empowering bold entrepreneurs we're
not productionizing the innovation needed to solve the critical, planet-scale
problems facing all of us.”
“Most investors find it hard to back businesses with
product-market fit risk, yet that is what deep tech entails.
Siraj Khaliq
Partner, Atomico
Member of the Board at arculus, PsiQuantum,
Graphcore, Scandit, and CloudNC
Page / 25
EuropeanStartups.co
Robotics
Examples of VC-backed deep tech categories & companies.
Semiconductors
Space tech
Energy
AI-first
enterprise
software
Advanced
materials
Quantum tech
AI-first life
sciences
Industrial
Medical
Agricultural
Restaurant & kitchen
Gaming, educational &
companion robots
Autonomous ground
vehicles
Autonomous flying cars
Drones
Drone software
Processing units for
machine intelligence
Sensors for AI-based
applications
Photonic integrated
circuits
Fusion energy
Hydrogen
Nuclear fission
Liquid-air energy
storage
Green battery cells &
systems
Carbon capture
Graphene
Ceramics
Renewable polymers
Plant-based plastic
alternatives
Robotic process
automation
Predictive maintenance
Computer vision &
cognitive video
automation
NLP-based decisions for
complex documents
Simulation & digital twins
Space telescopes
Satellites
Orbital launch vehicles
Space software
Space debris removal
Space propulsion
Satellite payloads
Ground stations
Antennas for space use
Computers
Software
Drug discovery &
development
Chemistry
Sensing
Security
Coatings
Blockchain
Security & infrastructure
Web-based platforms
for crypto transactions
Crypto compliance
Cold storage wallets
Business intelligence
Neuromorphic vision
systems
3D ultrasound sensors
Simulations
Photonics
Cryogenic
refrigeration
Cybersecurity
Cloud-based game
development platform
Datasets analysis &
molecular modelling
Analysis on research
databases
Clinical trials
Medical imaging &
diagnostics
Symptom checker for
triage & pre-diagnosis
Remote monitoring
Digital therapeutics
Autonomous vehicle
software
Various quantum
applications
AI for accident &
disaster recovery
Protein engineering
Cryptocurrencies
Decentralized finance
protocols
Antimicrobial plastics
Self-healing concrete
Ultracapacitors
New applications of Deep Tech are rapidly spreading
across different markets.
Combined valuation* ▊ <€3B+ ▊ €3‒8B+ ▊ >€8B+
Problem
solving
NLP &
interfacin
g
Prediction
Process
automatio
n
Robotics
&
autonomo
us
hardware
Sensors Engineeri
ng
Advanced
materials
Blockchai
n
Semicond
uctors
Generalist / horizontal DeepMind
Avora
Uipath, Celonis
Scandit, Varjo,
Ultrahaptics
Kiutra
Graphcore,
IQM, Beit
Providing healthcare
Dental
Monitoring,
Aiforia
Babylon
Babylon
Aidence
Lumeon
CMR
Robocath
MindMaze,
Varjo,
Visiopharm
Oxford
Nanopore
Parx Materials
FarmaTrust
NVision
Imaging
Technologies
Discovering medicine BenevolentAI
Causaly
Sophia
Genetics
Synthace,
LabGenius
Crispr
BioNTech
Molecule
Pharmacelera
Rahko
Food & Agriculture
Connecterra
QualySense
Naio, Tibot
Infarm,
Gamaya
Nicefiller,
Lactips,
Calyxia
Energy Greyparrot
Kayrros
Earth Science
Analytics
Flyability
Greyparrot
Tokamak
HT Materials
Science
Efforce
Fintech & legal
Tractable,
Omni:us
Eigen
Technologies
Cytora
ComplyAdvant
age,
Nivaura
Nexo, Ledger,
Elliptic, LTO
Mobility
Navya,
FiveAI
Ravin.ai
Lilium, Einride
WayRay,
Blickfeld
Arrival,
Zeleros
Canatu
Manufacturing
Universal
Robots,
Arculus
Paragraf
Cybersecurity
AU10TIX
Darktrace
onfido
Crypto
Quantique, Nu
Quantum
Entertainment
Robo
wunderkind
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Page / 26
EuropeanStartups.co
Suranga Chandratillake
General Partner
Balderton Capital
“In addition to specific areas of Deep Tech
that Europe particularly excels at (Machine
Learning, Quantum, Robotics for example),
the
continent’s breadth of
scientific
research makes it an ideal place to build
companies that straddle disciplines —
Machine Learning applied to Life Sciences,
or Quantum applied to Material Sciences, for
example. As a result, Europe is home to many
of the most interesting Deep Tech companies
in the world, and we expect the opportunities
for investment to continue to increase.”
Source: Dealroom.co. * Indicative.
Finland, Norway and Belgium have the highest relative concentration of Deep Tech
in the EU-27. Germany (Munich & Berlin) and France (Paris) lead by absolute size.
Page / 27
* London Deep Tech cluster includes Imperial College, University College, plus VCs and global champions.
“When it comes to early stage government
funding, Finland and Sweden are probably
best-in-class. Speed and minimal bureaucracy,
and some of the best outcomes as a result. EU
countries should take a close look at what
works there, learn from it, and replicate it. ”
Rodolfo Rosini
CEO
Undead
Deep Tech VC investment
2015–2020
Deep tech as % of VC
invested (2015–2020)
Important Deep Tech clusters
UK
Oxford-Culham-Harwell-Abingdon, Cambridge,
Bristol, Dundee, Warwick, Southampton, Edinburgh,
London*
Germany
Berlin, TU Munich, Fraunhofer, KIT, RWTH Aachen
University, Uni Mainz, Darmstadt University of
Technology, Ulm, German Aerospace Center
France
Paris, CEA (Atomic Energy Commission), Vision
Institute, LNE-SYRTE, LP2N, Grenoble Institute of
Technology, Inria, Sorbonne (incl. ISIR)
Sweden
Lund, KTH Royal Institute of Technology, Luleå
University of Technology, Uppsala, Karolinska
Institute, Chalmers,
Switzerland
ETH Zurich, Swiss Federal Institute of Technology
Lausanne, EPFL, IDSIA, UZH
Netherlands
Eindhoven/Brainport-ASML-NXP-Philips,
Delft, Wageningen, TNO, University of Amsterdam,
Twente
Finland €
VTT, Aalto, Oulu, University of Helsinki
Belgium
Ghent, Leuven-Imec, Hasselt, Antwerp, UCLouvain,
Vrije Universiteit Brussel
Ireland
Limerick, Dublin
Spain
Starlab, Polytechnic University of Catalonia (incl.
ICFO)
Denmark
Odense, University of Copenhagen, SDU
Norway
NTNU
Italy
University of Milan, Politecnico Milano
Austria
Tu Wien, University of Applied Sciences Technikum
Wien
Poland
Warsaw University of Technology, Wroclaw
University of Science and Technology, Polish Center
for Technology Development
Estonia
University of Tartu
19%
38%
29%
24%
26%
33%
32%
25%
23%
21%
18%
37%
19%
15%
23%
16%
€5.4B
€5.0B
€2.5B
€2.5B
€1.2B
€1.2B
€0.9B
€0.8B
€0.7B
€0.6B
€0.6B
€0.5B
€0.3B
€0.2B
€0.1B
€12.6B
3 Competing globally in the age of
Deep Tech.
$16B
DeepMind, Project Baseline, Verily Life
Sciences, quantum computing,
Waymo, Stratospheric balloons for
rural internet
$23B
Including AWS, Alexa, Amazon Go
(Cashierless store), Prime Air (drone
delivery)
$8B
Including Blockchain, React.js, AI,
Reality Labs (Oculus AR/VR), Rural
Access
$12B
Autonomous vehicle system, Mobile
Augmented Reality, Biometric sensing
Page / 29
Source: PwC
Amazon
Alphabet
Volkswagen
Samsung
Intel
Microsoft
Global R&D spend 2018
█ Europe (incl. UK)
$23B
Apple
Roche
Johnson & Johnson
Merck & Co
Toyota
Novartis
Ford
Facebook
Pfizer
General Motors
Daimler
Honda
Sanofi
Siemens
Oracle
Cisco
GSK
Celgene
BMW
Nokia
Exor
IBM
QUALCOMM
AstraZeneca
$10B
Big Tech dominates R&D spending, investing to accelerate
growth and in new products. Volkswagen has a huge R&D
budget but still mostly spends on combustion engine
research. Meanwhile, Elon Musk shows that total budget is
not everything and disruption is possible.
$20B
$5B
$15B
€5.1B
€0.8B
€210M
€350M
n/a
€140M
€1.8B
€210M
Note: R&D budget in 2018 as per PwC.
AI has so far favoured Big Tech incumbents
with data, rather than disrupt them.
Source: Dealroom.co based on discussion with Stephen Nundy from Lakestar and others. Stages based on Technology Readiness Levels used by governments.
Page / 30
Europe’s big corporate R&D budgets are concentrated around pharma, automotive
and telecom. The USA dominates internet, software and electronic hardware.
Corporate R&D spend in 2018 ($ billions)
United
States
EU-27
Japan
China
South
Korea
United
Kingdom
Internet, software, hardware
(Google, Apple, FB, Amazon, Samsung)
114
9
9
15
17
1
Semiconductors
(Intel, NXP)
39
5
3
1
2
0
Biotech
(Celgene, Abbvie, Gilead, Amgen)
35
4
0
0
0
0
Pharma
(Roche, J&J, Merck)
40
42
13
1
0
12
Automotive
(Volkswagen, Toyota, Ford)
19
46
39
6
4
4
Telecom
(NTT, Nokia, Eriksson)
13
16
2
3
0
1
Oil & Gas
(PetroChina, Exxon, Shell)
1
3
0
3
0
0
Dominated by USA big tech. These are
domains where money is spent on
futuristic moonshots.
Europe has strong position in Pharma
and Automotive.
Very low R&D spending. And 90% of
that low spending goes to fossil fuels.
Opportunity to grow?
Attracting top talent (Palantir,
DeepMind, Crispr, UiPath)
Cutting edge technology, data
accumulation and capex heavy
(Waymo, SpaceX, AWS)
Some AI-first software companies end
up as quasi-services businesses (lower
margins, scaling challenges,
commoditized AI models, heavy cloud
costs, as described in detail by a16z).
Examples include manufacture of
autonomous robots, self-driving cars
(complex hardware which, given time
and capital, can become widely
accessible).
Page / 31
Source: Dealroom.co
* Babylon = also adding own doctors.
** Tesla quadrant depends on how fast car industry can catch up.
Most tech eventually becomes widely accessible. Therefore,
companies need much more than just IP to succeed.
Capex
light
Capex
heavy
Data accumulation /
early-mover advantage
No data / early-mover
advantage
Babylon*
Tesla**
“Deep Tech
in combination with
platforms that can accumulate large
new datasets is driving innovation.
“For instance, telemedicine platforms
collecting written data through providing
their service can create products based
on NLP; or startups using AI for drug
discovery are collaborating with pharma
companies, and can gain insights and
data to refine their algorithms and
develop their own products.
“You can expect to see M&A and
partnerships along the way as these
business models evolve.”
Dr. Inga Deakin
Principal, Draper Esprit
Health Tech investor
Source: Dealroom.co
Page / 32
€33B
€39B
€33B
USA
€7.0B
€9.5B €9.4B
Europe (incl UK)
€15.7B
€7.5B
€6.1B
China
€21B
€13.6B
€5.3B
2018
2017
2019
2020E
2018
2017
2019
2020E
2018
2017
2019
2020E
Venture capital investment in Deep Tech by destination
While VC investment in European Deep Tech has
overtaken China, the full picture is different.
China’s government is making additional investments
on a national level. For instance, it is reportedly
spending $10 billion on a centre devoted to quantum
computing and artificial intelligence. Russia has a
similar initiative albeit on a smaller scale.
“Even after streamlining R&D funding in
Europe, we still need a DARPA-type entity
that can fund long-term strategic technology
with
limited bureaucracy and a clear
mandate to take risks, in fields where the
private sector has not started investing yet.
There will certainly be money wasted in the
beginning (which is exactly what happened
with DARPA in the first decade) so this
doesn't need to be huge, but it needs to be
staffed with top talent.
“Today there are technologies that are going
to become important in 2035+ where Europe
is currently not playing a sufficient role
outside academia, similar
to quantum
computing 5-10 years ago.”
Rodolfo Rosini
CEO
Undead
Europe’s universities and spinouts.
Deep Tech spinouts by university
Nathan Benaich
Founder & General Partner
Air Street Capital
“University graduates and their research are key engines for
entrepreneurship. In contrast to their US peers, UK Universities seem
to prioritise rent-seeking over long-term success stories that see
founders reinvest in their ecosystem. Entrepreneurs are expected to
build global winners while they're hamstrung with punitive equity
ownership structures and expensive IP licenses and royalties from
day one. We need a permissive, not punitive, environment for
European spinouts.
“We need to rewrite the University spinout protocols in Europe.
Today, many new founders spend months to a year+ mired in
bureaucratic negotiations. In the US, 3-5% simple equity ownership
upon incorporation is typical; the UK can be 10x greater. This is
entirely deterring many would-be founders from pursuing their
entrepreneurial ambitions. Instead, Universities should offer a simple
deal for founders to spinout with minimal friction and the best shot at
building long-term market leading companies. “
Interactive landscape of top universities including Oxford,
Cambridge, ETH Zurich, TU Munich, Lund, Delft, Leuven, Aalto,
Eindhoven, and many others.
Page / 33
EuropeanStartups.co
“We need to rewrite the university
spinout protocols in Europe.

Page / 34
EuropeanStartups.co
EU
China
43%
20%
High share of highly-cited research publications
Europe
France
UK
Spain
USA
Italy
35%
28%
26%
23%
22%
18%
Germany
38%
USA
Taken from Benedict Evans / Mosaic Ventures Dec 2020.
Data originally from BEIS/SCOPUS/UNESCO/THE 2020.
Europe does well in Computer Science ranking (THE 2020)
European students are more into Science
(portion of graduates in Science, Technology, Engineering, and Mathematics)
1. Oxford
11. Singapore National
2. Stanford
12. UCLA
3. ETH Zurich
13. Singapore Nanyang
4. MIT
14. Cornell
5. Cambridge
15. Tsinghua (Beijing)
6. CMU
16. Georgia Tech
7. Imperial College London
17. HKUST
8. Harvard
18. TU Munich
9. Princeton
19. University College London
10. Caltech
20. École polytechnique fédérale de Lausanne
“Europe is world-class in research.
European universities and ecosystems
can help close the gap by fostering an
entrepreneurial culture.
Dr. Inga Deakin
Principal & Health Tech investor
Draper Esprit
“In both the US and UK, experienced entrepreneurial academics,
who want to spin out a second company with university IP, have a
lot of leverage with their university tech transfer offices for a fast
and favourable transaction. First time academic entrepreneurs
often don’t know what to expect, don’t know what is most
commercially important, and would benefit from discussions with
peers and others outside the university to help with negotiations
within their university. European universities and ecosystems can
help close the gap by fostering an entrepreneurial culture and
training this larger group of researchers.“
UK
4 From Deep Tech to Deep Purpose.
Page / 36
An effective Deep Tech strategy needs to focus not only on the
technology, but on commercial success, i.e. building things
people want to use. Using technologies with such huge
transformational power, deep tech startups also have the
potential to solve global challenges.
Global warming
(e.g. fusion)
Curing diseases & fixing
healthcare (Crispr, robo
advice, ….)
Transforming industry
(e.g. autonomous robots)
Food sustainability
(e.g. precision farming)
It’s time to build…, but what to focus on?
Things
people really
want
Deep
tech
Solving
global
challenges
Enabling Deep Tech:
quantum technologies and semiconductors.
2018
Espoo, Finland
€156—234M
€39M Series A in Nov 2020
60+ startups enabling deep tech
Deep Tech working on climate
100+ Deep Tech impact startups »
2009
Abingdon, UK
€316—475M
$87M Late VC in Jan 2020
Visit 170+ startups
Deep Tech for drug discovery &
development.
2016
Paris, France
€125M
$43M Series A in July 2020

Robotics to transform industry, medical,
and agricultural processes.
2015
Croix, France
€327—491M
$90M Series C in Sept 2020
150+ robotics startups