On our way to

technological singularity

The European Artificial Intelligence Landscape | More than 400 AI companies built in Europe

Software is eating the world and Artificial Intelligence (AI) is at the heart of this takeover. Since we at Asgard are deeply involved in the European AI market, we thought we would share our insights.

Main findings:

  • Europe has a growing and thriving Artificial Intelligence industry
  • The UK has by far the strongest AI ecosystem, followed by Germany, France and Spain
  • London is Europe’s number one hub for AI companies, followed by Berlin, Paris, Madrid, Stockholm and Amsterdam
  • Switzerland has the most AI companies per citizen
  • Most AI companies are in the data analytics market
  • There are some mature and well-funded AI companies in Europe
  • Only 60% of companies claiming to be AI firms actually are

Get the full list of all 409 European AI companies for free

The European Artificial Intelligence Landscape and largest AI hubs in Europe

 European Artificial Intelligence Hubs and Landscape

The European Artificial Intelligence Landscape – click here for a higher resolution

The United Kingdom takes the lead as the strongest AI ecosystem in Europe. We have counted 121 AI firms in the UK, with London clearly the largest hub.

In second place is Germany (51), with Berlin as the main AI hub supporting 30 AI companies.

France (39) and Spain (31) follow in third and fourth place.

European Artificial Intelligence Nations

There are also growing AI industries in Switzerland (21), Sweden (19) and the Netherlands (17).

Italy (14), Russia (13) and Finland (11) follow.

AI companies from the UK, Germany and France account for over 50 % of the European total. These numbers are not surprising given their more mature digital ecosystems, a requirement for growing complex AI companies.

European Artificial Intelligence companies by country size

Switzerland has the Most AI Companies Per Capita

An interesting side note is that some countries perform better when taking population into account. In this case, Switzerland leads the field, followed by Finland, the UK, Sweden, Ireland and Denmark. The UK is an outlier here as Spain, Germany and France all have significantly fewer AI companies per citizen.

European Artificial Intelligence Industries

Data Analytics Companies Dominate European AI Industries

Data Analytics companies make up the bulk of AI firms in Europe, perhaps due to AI needing data and its emergence from the Cloud and Big Data trends of recent years.

Sales & Marketing AI firms tend to solve well-known problems with this new abundance of data, and take advantage of improvements in NLP (natural language processing) and NLG (natural language generation) within the mobile / IoT world. We therefore see many new companies in the fields of Text Analytics and Conversational AI.

Customer Service and Personal Assistants have been very popular fields in which to start companies, supported by the advances in frameworks and free APIs.

Robotics is one of the oldest fields to use AI. However, we are not yet seeing an increase in the number of robotics companies.

On the other hand, we still have too few companies in the fields of Logistics, Education, and Travel using Artificial Intelligence.

Best funded European Artificial Intelligence companies

Best Funded European AI Companies

Once a firm’s technology becomes a commodity, it becomes difficult to remain an AI company. Many grow out of their AI definition and develop into something else. However, we have identified ten companies which still run as AI companies, even after larger funding rounds.













Data & Process

We compiled a list of 715 companies based in Europe claiming to be in the AI industry. We took the data from Crunchbase, AngelList, and our own research.

We then excluded companies which are inactive, agencies, consultancies, have been acquired, have a closed beta, or do not use machine learning. Additionally we attempted to exclude those which appeared only to use AI as a marketing tool, adopting buzz words such as “customer intelligence”, “marketing automation”, and “big data optimization”.

We may have missed some companies out, for example if they are too young, in stealth, or if we simply never heard of them. We apologise for this and will include them next time – just send us an email to contact@asgard.vc.

What is Artificial Intelligence? The definition is constantly changing. What we see as AI today could be standard software next year.

To get the list of all 409 AI companies, click here.


If you are interested in meeting European AI entrepreneurs, researchers and thought leaders, then join us for our Rise of AI 2018 conference.


Many thanks to Milette for investing weeks of her time to generate the data. Unfortunately, there is as yet no AI for identifying AI companies.

The European Artificial Intelligence companies list | from 2017

We have compiled a list of 409 European Artificial Intelligence companies. Each company has a crunchbase link, industry, webpage, city and country.

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Evolving from Narrow Artificial Intelligence to Cognitive Artificial Intelligence

Much has been written about the Rise of AI and it is more to read than you have human time to do it. I have personally written about AI First and the next stage of machine intelligence back in 2015. Today I commit some words about where Artificial Intelligence is today and where it is heading to in the next years. At the end I have a wish list for entrepreneurs, companies and researchers.

Today we are already living in an AI world

Big Data, machine learning, hardware and the Internet have enabled us to create hundred thousands of different Artificial Intelligence applications.

We use AI for automation of processes. We let it trade stocks, drive cars, trucks, control trains, drones and submarines. We let it analyse traffic videos. AI sorts for us our Facebook, Spotify and Netflix content.

We use AI for human machine communication. Either with Google Speech or we communicate directly with Alexa, Cortana and Siri. We even let AI read and write our emails.

Artificial Intelligence is the digitalization of human knowledge work. We trust AI for navigation and research. We even let AI win Go, poker, compose music and create art.

And that all is just the beginning. It is like DOS for the PC era and a Nokia 3210 for the mobile era.

Today we have Narrow Artificial Intelligence

I call these current systems Narrow Artificial Intelligence. They are highly specialized and are often better than humans at the same task. However they need large sets of data and weeks/months/years of training by humans. Additional most models are still highly mathematical (e.g. try to improve gradient descent) and brute forcing trial & error (see error back propagation).

On top the biggest drawback is, that these Narrow Artificial Intelligences can not transfer knowledge.

The field of AI is as old as the field of computers. We started with heuristic systems, then we had expert systems and today we have learning systems. However that is not enough and we need to reach the next stage of machine intelligence.

We need AIs, which can adapt to new situations. We need AIs which can build a memory, gain knowledge and uses its own experiences. We need AIs, which learn faster with less data.

What we need is Cognititve Artificial Intelligence

I call the next generation Cognitive Systems, or Cognitive Artificial Intelligence. These are a combination of machine learning + knowledge technologies. Prof. Hans Uszkoreit briefly touches that topic at the end of his Rise of AI talk.

A Cognitive Artificial Intelligence has perception (sensory input like hearing, listening, reading, seeing, feeling). It can execute action (interpretation, reasoning, planning and communication) and it can react to unplanned situations.

For Cognitive Artificial Intelligence Systems we need learning algorithms, which are faster and need less data (better abstraction). We also need to better understand how our own brain works. Humans are still the only Superintelligence in the room.

My AI wish list

I kindly ask researchers to work more on transfer knowledge. Google’s PathNet leads the direction. Please work more on AI’s memory and experiences. Find ways that AIs can react to unplanned situations without brute forcing their way to optimization.

For entrepreneurs and startups out there: Work on models and the data. You need to have access to plenty of data or own it. Close the feedback look in your AI system. Means, your system should gather, learn and optimize without human help.

Algorithms and frameworks are free. Concentrate on the models, which are compressing your data. Dr. Damian Borth speaks about it at his Rise of AI talk.

For the more mature companies: think AI first. Build internal AI teams, buy AI companies or partner with AI startups.

If you have a service, then sell the solution. Fix your problems and your customer’s problems with AI.

If you sell hardware, then use your hardware as a Trojan Horse for your (software) intelligence.

This is my AI wish list for 2017.

Organizing one of Europe’s largest conferences for Artificial Intelligence: RISE OF AI 2017

Hosting a conference is not an easy task. And I find many similarities to run a startup. You need funding, a strong team, a concept, a business model, traction, marketing and execution.

Therefore I would like to share my insights in organizing one of Europe’s first and largest conferences for Artificial Intelligence in Berlin: Rise of AI.

Briefly about me: I am an investor into AI and I like to speak & write about AI.

It started small a few years ago. At the beginning we where 15 people meeting at cbase in Berlin for one evening. We discussed Ray Kurzweil and his theory of the Singularity. I decided to give the concept a greater platform to reach more people. I hosted the first Rise of AI meetup with 70 people and then six months later again with 180 people. Both evenings we had great talks and a waiting list of 700 interested ones. There seemed to be a demand.

So far so good. I decided last September to make Rise of AI a full day conference. Mainly because I want to place Berlin on the map for Artificial Intelligence, to connected the greatest minds and to prepare humanity for the upcoming Rise of Artificial Intelligences.

Like with a startup, you beginn with the team.

A small and powerful team

I didn’t think much and asked my wife right away. She is an event manager for 10 years and runs her own agency for digital clients. I have the vision and network, but she has the operational skills. We can call her the COO, while I took over as CEO & CFO. My task was the program, speakers, partnerships, website, financials and ticket sales. Veronika was in charge for every other detail like catering, location, design, HR or furniture. While it sounds minor, she did the major part of the work.

We worked together not only, because she is a professionell and has great experiences. Additional because I like to work with those, who I trust. I run my investment firm with my father; my conference with my wife and my political activities with my sister.

Pick the right date

You will never find a date, where there won’t be other events. However I tried to avoid events the same day, where my potential guests would rather go to. Therefore I compiled a list of 200 events and analzed their ticket prices, content, strategy, target group, partners, place and date.

Conference season begins in September and Ends in June. We opted for May, since Berlin is the most beautiful in May. Additional there were no larger AI conference announced for May at this time.

Find the a location which fits your needs

Normally finding a great location is tricky. Most event spaces are too small, too expensive or already booked. It takes a lot of time to research them and to visit the spaces.

We finally chose the Deutsches Technikmuseum Berlin. It was perfect, since it has room for 350 people and fits wonderful to the storyline talking about Artificial Intelligence. Where else can you speak about the future when not at the place, where it was created? For example you could see the (re)build of the Z3 there – the first programmable computer build in the 1930s/1940s by Conrad Zuse.

No concept no conference

Similar to a business plan, you need a concept for you vision, mission and milestones. Who do you want to target? What shall be the content? Who can speak about these topics?

I have worked for months on the concept and it never has been finished. It was important for me to have a storyline:

  • What is Artificial Intelligence?
  • What is the Future of Artificial Intelligence?
  • What are the implications of the Rise of Artificial Intelligence?

First we start in the present, then speak about the future and its consequences.

Furthermore it was important for me to invite those, who know something about AI (scientists and entrepreneurs) and to connect them with those, who would like to learn more (politicians, journalists, top level managers).

In retrospective I have to admit, that politicians do not care for the future, technologies and Artificial Intelligence. Each of them passed on us.

The media was more interested, but inviting journalists sucks. The had the highest no-show quota (people who have a ticket and do not show up). First (many, but not all of them) write you an email with demands. Then they threaten you do write a negative article in their (dying) newspaper, if you do not invite them FOR FREE. Third they get a ticket but do not show up.

I have made better experiences with bloggers.

Content is King

Like for SEO, content is king at conference. Most conference I have visited (>100), the content was not strong enough. Therefore I intended to change that.

I prepared a long list of speakers and checked everyone of them: personal interview, hours of youtube talks, obtaining references and narrowing down possible topics.

That was the part of the organizing, which I enjoyed most. Within my network I was able to win many speakers. Since I am active in the Artificial Intelligence industry, it is easier for me to judge the competence of possible speakers.

By the way it is difficult to win comparable qualified female speakers. There are just significantly more men in the AI business. Nevertheless we emphasized to integrate woman in our content program.

Additional it is hard to find a lighthouse speaker. A lighthouse speaker is someone, everyone knows. The only person everyone wanted to see, was Elon Musk. However even I asked Elon politely, he did not react. I understand that. I would be busy too, if I would build rockets, autonomous cars, send people to Mars, work on Brain Computer Interfaces, dig tunnels, stop the AI apocalypse and fight global warming.

Winning partners is sales

To win a partner is similar to customer sales. If you get a deal, everyone is happy. However it takes a lot of time to make that happen. Sales Cycles were between 2 weeks and 4 months. I had to speak with hundreds of peoples before we closed it down with four partners (KPMG, IBB, HTGF, Axel Springer). I am very thankful for their support, since they helped us to pre-finance the event.

As usual I created a CRM, a lead list and funnel for sales. Partners received from us a combination of tickets, branding and content collaboration.

Always be selling tickets

Really. Sales almost never stops. You start on day one with crazy early bird and most often you sell until the event day. However we were lucky to be sold out a few weeks before the event.

I loved the moment when eventbrite sent me an email, that someone bought a ticket. It reminded my at my former business of selling wedding-dresses. I guess successful sales gives you a boost of dopamine.

There is no golden rule how to sell tickets. Even I tried a lot, no channel was scalable and 100 % trackable. Therefore I used a combination of discounts, personal invitation, facebook, adwords, SEO, cooperations and word-of-mouth. If you know how to sell tickets easier, please let me know.

Events are expensive

For a one day conference you can spend >100k €. If you care for the security and well-being of your guests, nothing should be cheap.

First you need a location and for >350 people, the costs are often 10,000 € to 35,000 € per day. You need the location one day before (for installation), during the event day and one day after (disassembly). That makes three days you have to pay for.

Second catering is expensive. You have to calculate between 50 € and 100 € per person per day, depending on the quality. If it is cheaper, you should not eat it.

Third you have to pay for the electronic equipment. You need a stage, screens, monitors, lighting, beamers, wiring and several technical people during the event and the days before and after.

Then you have to rent furnitures, chairs, tables and lounges. They have to be shipped, assembled and disassembled.

You need some funding for performance market. Additional you should treat your speakers well.

You should not forget insurances, since you rent equipment worth millions. You have to pay fees for certification, applications and safety concept.

Next you have to hire the temporary staff. That includes hostesses for check-in, cash desk, cloakroom, beverages, food, speaker management and cleaning. Additional you need security guards before, during and after the event.

Additional there are hundreds of minor costs, which will show in your profit loss statement: like designer, printing, name tags, logos, garbage collection, event app, speaker presents and floral arrangements.

If you do not have experiences with events, you will most likely forget plenty of things you need. Furthermore there is the risk, that service contractors will not offer you the best possible deal.

You have to pre-finance your conference

To reach break-even is hard and a very important milestone. However more concentration you need for the liquidity management. Ticket sales tend to come in late but most costs occur before. You have to make advance payments for furnitures, equipment and service providers. Additional you face the risk, that one of your service providers go bankrupt and you lose your money.

On top the costs are always higher than expect. Insurances, fees, paper work and other unexpected expensive will have to be paid.

Therefore it is important to have partnership and sell early bird tickets. Even the early bird tickets are sold with a negative contribution margin.

An interesting side fact is, that most guests get the maths wrong. They take the highest ticket price and multiple it with the expected number of guests. The truth is, that 95 % of guests go for the cheapest ticket, 4.8 % buy the middle one and 0.2 % take a premium ticket.

We got something right

It was right to work with my wife. She is a great business partner and I could not have done it without her.

It was right to start early. After the event is before the event. No time to loose.

It was right to give everything. You are never finished.

It was right to invest in content and great speakers.

It was right to support networking amongst our guests.

It was right, how we did marketing. I really do not know what worked well, but since we were sold-out, something had worked.

However we have areas to improve

Mistakes are made. I messed up the ticketing system internally. Instead of creating tickets for speakers, partners, media, team and paying guests; I sorted the tickets from business perspective (going after price). That made operations a bit more complex.

Additional I underestimated the amount of late ticket buyers and partners. Many people wanted to join, when we were sold out.

It is interesting to observe, that even you invite people every month for half a year, they “forget” to buy their ticket and then ask for it on the day of the event.

Some people do not read emails and then complain about lack of information. Do they expect I call them? Sorry, but we don’t have an AI for that yet.

We had a system with catering coins. The idea was to provide food and beverages faster. However it did not work out as expected. We won’t do it again.

Speakers were great but limited in depth. I have a long list of topics I was not able to cover. For 2018 our program will try to fix that.

Our target group was not narrow enough. We had a wonderful mixture of people (corporate CEOs ate lunch with Transhumanists), but for networking that was not optimal.

Rise of AI 2018 – learn how to apply Artificial Intelligence

What are our next steps? Preparation for 2018 has already started.

For 2018 we would like to grow to 500 people – again in Berlin. I will introduce a second stage for more depths.

Stage one will be for Artificial Intelligence Vision:

  • What is Artificial Intelligence today?
  • How to create ethical and safe AI?
  • Consequences from the Rise of AI for society?
  • Strategies and Use of AIs
  • Regulation and support of AI systems
  • Should AIs be allowed to lie?

Stage two will be for Artificial Intelligence Applied.

  • What is the progress in deep learning and transfer learning?
  • How do I build an AI?
  • How do I use AI in my company?
  • Use cases from experts, who have build AIs before.

In case you would like to joins us for Rise of 2018, then sign up at www.riseof.ai to get an early invitation and the best offers.

Following some impressions:

The German Artificial Intelligence Landscape

click for a higher resolution of the map

As a Venture Capital firm for Artificial Intelligence we follow the growing AI market closely. For the German AI Landscape Map, we created a list of over 600 European AI startups based on internal research mainly deriving from our network and Crunchbase.

Not every company that lists AI as a part of their product has AI in it. We have therefore taken the freedom to clean the raw data. We’ve ended up with 81 German Artificial Intelligence startups, which made it onto our map.

Most founders solve well-known problems with AI

We observe that the largest fields for AI startups in Germany are:

  • Customer support
  • Customer communication
  • Sales & marketing
  • Software development
  • Computer Vision / Image recognition

These five categories account for 48 % of German AI startups.

German AI categories

Since software engineers are closer to the topics machine learning and computer vision, they are more likely to start an AI company than others. We therefore see a large group of the companies with computer vision as their main product. Computer vision is one of the oldest fields of the new wave of deep learning technologies. This field already has a wide variety of software and datasets available so it is a more obvious market to pursue.  

Customer support, sales, marketing and customer communication are also easy pickings. Non-technical founders often end up choosing one of these markets to set up their new startup.

On the other hand, we only have a few companies in the space of automotive, legal, industrial, supply chain, security, and logistics. Many founders lack the industry insights to pursue the real problems in an industry and therefore struggle to build a new solution for it.

Half of Germany’s AI startups are located in Berlin

Berlin is leading with 54 % of all German AI companies, followed by Munich, Hamburg and Frankfurt Am Main.  

German AI cities

Berlin is the fourth largest global AI hub

On a global scale, North America have the most AI companies (921), ahead of Europe (632) and Asia (258).

Global AI startups

Silicon Valley is the strongest AI hub, followed by London, Paris and then Berlin.

Global AI hubs

In the European AI landscape, UK is the strongest, with London being the major hub. Germany is second, followed by the Nordics, France, Benelux and a long-tail of other European ecosystems.

European AI Landscape

The European AI landscape is growing but it is still very much in its infancy. To further strengthen the European and German AI landscape we need to build strong startups in new sectors and markets. We also need to build a healthy ecosystem and nurture the local scenes inside Europe.

One of our initiatives to pursue this goal is to arrange an AI conference in Berlin.

If you like to connect with AI companies, AI investors and journalists, you are invited to join our conference Rise of AI in May 2017.


If your startup is missing on the list below, please contact us.

These are the German AI companies we have identified and sorted by category:


German Auto Labs – https://www.germanautolabs.com


Business Intelligence

Mapegy – http://www.mapegy.com

12k Research – https://12k.co

Fedger – https://fedger.io


Customer Communication

WunderAI – http://wunder.ai

chatShopper – http://www.chatshopper.com

149 Technologies – http://www.149tech.com

Yones – http://www.yones.net

e-bot7 – http://e-bot7.com

Gigaaa – https://gigaaa.com

Kweak.ly – http://kweak.ly

Unified Inbox – http://unifiedinbox.com


Customer Support

Parlamind – https://parlamind.com

Aaron – https://aaron.ai

Twyla – http://twylahelps.com

Fredknows.it – http://www.fredknows.IT

Sematell – http://www.sematell.com


Data Analytics

Leverton – https://leverton.de

Inspirient – http://www.inspirient.com



Fraugster – https://www.fraugster.com

Sentifi – https://sentifi.com

Risk Ident – https://riskident.com

CollectAI – http://www.collect.ai



stickIT – www.getstick.it

Xbird – http://www.xbird.io

Heuro Labs – http://www.heurolabs.com

Healthcare X.0 – http://www.healthcare-xnull.com

Kaia Health – http://www.kaia-health.com

MedX – http://medx.net


Human Ressources

MoBerries – https://www.moberries.com

12grapes – https://www.start12grapes.com

Job Pal – https://pal.chat

JobBot.me – http://www.jobbot.me


Image Recognition

EyeEm – http://www.eyeem.com

Twenty Billion Neurons – https://www.twentybn.com

Searchink – http://searchink.com

Tiresio – http://www.tiresio.com

Wizart – http://wizart.io

Peat – http://peat.technology

Terraloupe – http://www.terraloupe.com

Planet – http://www.planet.de

Picalike – http://www.picalike.com



Merantix – http://merantix.com



MotionsCloud – http://motionscloud.com



Synergist.io – https://www.synergist.io



Cargoness – https://www.cargonexx.de


Process Automation

Micropsi Industries – http://www.micropsi-industries.com

Sota Solutions – http://sota-solutions.de

Arago – https://www.arago.co

Konux – http://konux.com

5Analytics – http://www.5analytics.com

N-Join – http://www.n-join.com



Caspian Robotics – http://caspian.io

Kewazo – http://kewazo.com/

Xamla – http://xamla.com

Proboter Robotics – http://proboter.com


Sales & Marketing

EyeQuant – http://eyequant.com

So1 – http://www.so1.net

Pivii – https://pivii.co

The SaaS Co. – http://www.thesaas.co

Inbot – www.inbot.io

Goedle.io – http://goedle.io

Qymatix Solutions – https://qymatix.de

Adtelligence – http://www.adtelligence.de



Versus- http://versus.com

Aivy – https://aivy.io

Feelyt – https://www.feel.yt



AVA – http://www.ava.info

Neokami – https://www.neokami.com


Software Development

Deckard AI – http://www.deckard.ai

Heili – http://www.heilihq.com

Lastmile – http://golastmile.com

Weps – http://getweps.com

Lateral – https://lateral.io

Autumn AI – http://autumnai.com

Explosion AI – https://explosion.ai

Spacy – https://spacy.io

Acellere – http://www.acellere.com

Simspark – http://www.simspark.com


Supply Chain

Evertracker – http://www.evertracker.com



Voya Travel – https://voya.ai


Created by Fabian Westerheide & Lars Holdhus – Asgard – smart VC for AI – Berlin – 2017