The German Artificial Intelligence Landscape

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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 –


Business Intelligence

Mapegy –

12k Research –

Fedger –


Customer Communication

WunderAI –

chatShopper –

149 Technologies –

Yones –

e-bot7 –

Gigaaa – –

Unified Inbox –


Customer Support

Parlamind –

Aaron –

Twyla – – http://www.fredknows.IT

Sematell –


Data Analytics

Leverton –

Inspirient –



Fraugster –

Sentifi –

Risk Ident –

CollectAI –



stickIT –

Xbird –

Heuro Labs –

Healthcare X.0 –

Kaia Health –

MedX –


Human Ressources

MoBerries –

12grapes –

Job Pal – –


Image Recognition

EyeEm –

Twenty Billion Neurons –

Searchink –

Tiresio –

Wizart –

Peat –

Terraloupe –

Planet –

Picalike –



Merantix –



MotionsCloud –


Legal –



Cargoness –


Process Automation

Micropsi Industries –

Sota Solutions –

Arago –

Konux –

5Analytics –

N-Join –



Caspian Robotics –

Kewazo –

Xamla –

Proboter Robotics –


Sales & Marketing

EyeQuant –

So1 –

Pivii –

The SaaS Co. –

Inbot – –

Qymatix Solutions –

Adtelligence –




Aivy –

Feelyt –




Neokami –


Software Development

Deckard AI –

Heili –

Lastmile –

Weps –

Lateral –

Autumn AI –

Explosion AI –

Spacy –

Acellere –

Simspark –


Supply Chain

Evertracker –



Voya Travel –


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

AI First – Artificial Intelligence Is Taking off in 2017

From online-first to mobile-first, we are currently entering the phase of AI-first. Artificial Intelligence is the consequence of an online, digital, connected, mobile, data-driven, computerized world. Let me explain why.

The 5 Main Drives for the Rise of Artificial Intelligence

There are five main drivers supporting the current Rise of Artificial Intelligence.

The more data the better for Artificial Intelligence

Nowadays almost everything is based on data. We humans measure, store and analyse everything imaginable. Every machine is based on data, with everything ultimately reducing down to a zero or a one.

The amount of data we produce as humans and machines is increasing every year. The more data we produce, the more of it we can feed into Artificial Intelligence systems. Why? Because we need it. The more data generated, the more complex our environment gets. Artificial Intelligence helps us to reduce some of that complexity.

Cloud solutions have started a process in which data is no longer stored on just one physical server, but is accessible everywhere at all times. This means the data can be harnessed more easily and used by other software, including AIs. Some call it the API economy, and even now Machine-to-Machine (M2M) communication already creates more data than human-to-human communication.

Artificial Intelligence is embedded into hardware

Chips are the brains of computers and they are getting a lot smarter. Google builds its own AI chips, as do Microsoft and Nvidia. The special chips they create are suitable for running neural networks and other machine learning tools which can support smarter AIs.

Soon these chips will meet the Internet of Things wave. AI-strengthened chips will be integrated into mobile phones, tablets, cars, drones, vending machines, robots and TVs. We can expect an intelligence upgrade for electronic items.

Software becomes smarter and hybridized

Every day there are really smart people out there improving on tools to create Artificial Intelligences. We are also starting to see more and more hybrid systems which combine expert systems, machine learning, bots and deep learning.

Deep learning has been around for 15 years, but has only come to the public’s attention in the last 3 years. There are therefore still a lot of findings and research results to be analysed and applied to real-world problems.

Universities researching machine learning and cognitive systems are now getting more attention, funding, clients and applicants. The academic world is awakening from its hibernation.

It is going to be easy to build your own Artificial Intelligence

You want to build your own AI one day? Deepmind has opened their own open source lab. OpenAI offers Universe for training of AIs. Google also shares Tensorflow. You can also use Theano and Torch.

There are already plenty of tools and soon there will be even more. Day by day, creating, building and training Artificial Intelligence systems will become easier and easier until we reach a democratization of intelligence creation.

Capital follows the entrepreneurs into AI

Over the last two years we have seen a surge in AI companies. Not everything which is labelled AI contains an AI inside. Maybe 90% of the companies are applying machine learning, but they aren’t building a self-improving, cognitive system.

Nevertheless, the trend is very positive. And where the ideas are, the money follows. Americans VCs have poured billions of dollars into AI startups.

Google, Twitter, Intel, Apple, Microsoft, Salesforce, Facebook, eBay, Oracle – they have all recently purchased young AI companies.

Consequence of the Rise of Artificial Intelligences

New technologies always bring about change.

Four steps towards Artificial Intelligence

There are four steps for a company to reach Artificial Intelligence.

From Big Data to AI

Firstly, data needs to be collected, stored and analysed. This is outdated thinking and tells you something about the past.

Secondly, machines start to make predictions based on the data. These predictions help humans to make faster, easier and better decisions.

Thirdly, machines make predictions, execute them, measure the results and then change the inputs and constraints to optimize the output goal.

Fourthly, machines achieve automation. They are becoming motivated cognitive agents and are able to use their various learned behaviours to create new transferable knowledge.

Most (old-economy) companies are at stage one or below. They know they have data and start collecting it.

Many digital companies (ecommerce, mobile, gaming) work with their data and are often on stage two.

Google, Amazon, Facebook & Co are leading the applied AI fields. Some parts of their companies are on stage three.

Stage four will come. Some brilliant teams are working on it.

You have to train an Artificial Intelligence

Artificial Intelligence systems have to be trained. It’s no longer a case of programming them and thinking they’re finished. An AI is never finished. There is always more it can learn, get better at, improve and ultimately deepen its knowledge.

Modern AI is like a child. You have to teach the AI everything: how to understand text, how to watch videos, how to listen to audio or how to generate language.

Some fields are easier to learn, like computer vision. Other tasks are much harder, such as understanding text.

Artificial Intelligence is eating your business

The new wave of AIs, often implemented by digital companies and start-ups, will eat many smaller businesses for breakfast. AI is a horizontal technology. It is impacting many industries (logistics, automotive, pharmaceutical, insurances, media, manufacturing, retail), systems (networks, cities, states), companies and humans.

In general, AI achieves two things. It makes processes more efficient and it makes stupid machines smarter. A self-driving car is smarter than a human-driven car. Using the Google search algorithm is more efficient than going to the library.

A future with less human work

However, this leads to several challenges.

One challenge is that applied AIs will drive companies out of business, force political change and force individual humans to adapt.

The other challenge is that millions of tasks will be done by machines. New jobs will be created (e.g. machine trainers), and there will be less demand for human labour. Why? Because that is why we invent machines in the first place (watch my TEDx talk to learn more or read 22 jobs disappearing in future); so that they work for us.

Artificial Intelligence is neither evil nor bad. It is a tool we use to generate more wealth, more happiness and more health for humans on earth. But change is never comfortable. AI forces the human species to leave their current comfort zone.

AIs brute force experiences

So what else can we expect? AI systems are already developing their own languages and encryption methods. Other AIs are able to generate images and videos. There are plenty of exciting things coming to the market over the coming years.

We can assume that some technical problems will be overcome: unclean data, unstructured data, limited access to data and biased data.

Furthermore, machines struggle with high degrees of abstraction during their learning phases. Humans today still learn more efficiently than machines. To achieve similar levels of intelligence, we have to train machines with significantly more data. Google’s AlphaGo was only able to beat the human world champion at Go because the AI system practised by playing millions of games. Since AIs can learn faster and in parallel, they brute-force experiences.

Another academic challenge is to build cognitive systems which can generate transferrable knowledge. This means combining different modules of an (artificial) brain.

AI is good for humankind

Sure, there is more: AI-assisted teaching, the jobless future, income equality, personalized medicine, self-moving objects, personal assistants for everyone.

The wide application of Artificial Intelligence will lead to prosperity, lower energy costs, more mobility, free education, longer and healthier lives and increased luxury.

Currently, AI is a bit overhyped because Hollywood, Techcrunch and Journalists find it easier to write about AI than other topics. Nevertheless, the underlying trends are strong. AI won’t go away. We should look forward to and embrace it.

If you would like to have a full day of great insights into Artificial Intelligence, then join our conference Rise of AI May 2017 in Berlin. If you just like to talk, ping me via twitter. If you look for capital, then check out Asgard – human VC for AI.

7 reasons you should join us for Rise of AI 2017 – Artificial Intelligence conference in Berlin

Rise of AI is one full day to learn about the status of Artificial Intelligence, think about the future and discuss its implication for society. 7 reasons why you should join too.

Europe’s most exciting conference for Artificial Intelligence

We started small. First 20 people at cbase speaking about “Did Singularity already happen?“. Then 100 futurists met at hub:raum and spoke about “Rise of AI – The Singularity might be closer than you think“. Half a year later, 170 forward-thinkers came together at Betahaus for “Rise of AI – Human coexistence with Machines“.

Now we are hosting the third time Rise of AI ( for 350 guests. We organize an exciting, intellectual, inspiring and unique event about Artificial Intelligence here at Berlin. We invite the greatest minds to the Deutsches Technikmuseum to discuss, talk, network and understand.

7 reasons why you should come to Rise of AI

#1 Artificial Intelligence is critical

Currently everyone talks about AIs. But what are AIs? Elon Musks warns us, as well as Hawking and Gates. Do you understand what AIs can do today? Have you thought about the progress of AIs the next years? You should. It could be the last invention of human kind.

#2 Superhealth. Superhappiness. Superwealth.

Artificial Intelligence has influence on your health, your wealth, your personal happiness, your free time and your job. Are you only an observer and watch it rolling over? Or do you want to be active and influence the change!

#3 Strong content

We have invited really amazing speakers. Prof. von der Malsburg hat 50 years of AI experiences. William Hertling writes crazy-creative books about AI conquering the world (12 books you should read to prepare for Singularity). Dr. Trent McConaghy combines AI + blockchains and believes machines take over the world. Prof. Danko Nikolic is a brain researcher and does not agree with Trent. Joel will moderate the day. And even some members of the German Bundestag have signed up.

#4 Interactive program

Keynotes can be great, but knowledge goes only one way. Therefore we have organize AI-Topic-Leaders. These are small workshops, where you can discuss more current topics with experts. Accelerated Dynamics will show us some autonomous drones and AI-startups will give us demos of their products.

#5 Meet the speakers and network

I don’t like it, when after a talk the speaker disappears. Therefore our speakers will be at their tables and open for a more personal Q&A sessions. Use this opportunity to meet them.

Additional networking is key for us. There is plenty of time and reason to meet new people, learn, exchange ideas and make contacts.

#6 We have a mission

We (my wife and I) organize Rise of AI, because we have a mission. We want to educate about Artificial Intelligence. We wish, that AIs will help us humans to conquer the galaxy one day. AIs will make our lives better, longer and more convenient. Additional there are challenges and risks (from jobless future to superintelligence). We need to address them before it is too late. Therefore Rise of AI is a platform for interested people to meet, discuss and learn.

#7 Historical location to talk about the future

Where else do you want to talk about the future? The Deutsche Technikmuseum Berlin is a historical location, where the past meets the future. You can see the first computer (Z1 by Zuse) and other great inventions of human kind.

Deutsches Technikmuseum

Do you need more reasons? Then check out our speakers and our program.

Have a look at Rise of AI for the most recent program, workshops, companies and early bird tickets.

We offer an Human Venture Capital Analyst Internship in Berlin 2017

An internship at a Venture Capital firm is a pretty good start into the industry. You will see from a high level the newest ideas, meet amazing founders and get a great overview at markets. From there on you can build your career in Venture Capital, go back to university or start your own company. 

We offer an internship in Berlin for 2017. See below for more details.

You will learn how to become a VC

You will look at a few hundred young companies and learn to evaluate deals. You will understand how to asses markets, how to analyze business models and what to look for at teams. Furthermore you will understand the fundamentals of running an early stage investment company and its operations. You might even become an expert for Artificial Intelligence. We would like to see that.

You should work with us

You will mainly work with Fabian, our CEO (his blog, linkedin). He is driven, full of energy and charming. His partner is Dirk Westerheide; we are a family owned Venture Capital firm. We invest our own money.

Working with us has several advantages. First we give you a lot of liberties. We do not care, when you work or where you are. We will have personal meetings once or twice the week, and in between you are on your own. We prefer to communicate on the phone, whatsapp and using emails. We also use several SaaS solutions for our workflows.
Second we are very focused on Artificial Intelligence. Rather than being mediocre in everything, you can dig deep into one field of the future and have an impact.
Third we are a small team. You work face-to-face with the CEO. No layer between. Additional we love to share our experiences. You can learn a lot from us if you want.
Fourth we are all entrepreneurs. We have started companies before, we have invested in even more. We often act fast and execute things our own way.

You will see a lot of deals

First you will start to analyze deals we send you. You will learn how to evaluate them (market, product, team, competition, financials). The goal is that you help us to make investment decisions. Your opinion will be very important for us. You will have a huge influence on what deals we will consider closer. Second you will meet founders, go to meetups and increase your network. Third you will work on our brand, strategy and support us with possible fundraising for Asgard or our portfolio companies. Fourth you will help us to organize the most inspiring AI conference: Rise of AI (

We look for quick thinkers

We like it, if you are a quick thinker. You should be curious for new technologies, new solutions and new ideas. Being analytic helps a lot. Additional if you like to meet new people, that helps with networking. We are looking for A-Players. That means you are highly intelligent, driven and ambitious. You can work hard and are result orientated. You also should keep to timelines and can organize you own work day. However it should not feel like work for you. You should enjoy it, because we believe that being a VC is a really cool job.

You should speak english. German is a nice to have but not mandatory. You don’t have to live in Berlin for now or ever. However we like to meet you in person once a while, therefore it is recommended to be close to the German capital at least for the first months of your internship.

Most of you will have a business background, but this is not a must. In contrast we even prefer that you have a degree in computer science, philosophy,  mathematics or physics. If you mix that with some business skills, you are good to go.

Additional we highlight, that we support more female entrepreneurs and female Venture Capitalists in the industry. If you are a woman, please apply. You have good chances.

For legal reasons, I have to state that we consider each application neutral for gender, race and age. 

The basics you need to know

This internship will happen in Berlin + remote work. We will pay you enough for rent, food and living. It shall start in 2017, however we are flexible on the actual day. We also consider to make a full-time offer after the internship, but that totally depends on you. The duration should be between 3 and 6 months.

How you can apply

We recommend that you read a bit about us before. Check our website. Check out our portfolio. Maybe check the Partners profiles. We are interested in people, who would like to invest in the most amazing AI companies. If you see a fit and have read the above text, then send us an email to (Fabian will receive your message) or apply directly here.

What will come next?

We will screen every application for completion and internal criteria. The best will receive questions, which you may answer within a given time. An video interview will be the next step. Afterwards we may make you an offer.

About Asgard

Asgard provides early stage Venture Capital for Artificial Intelligence. We are family owned and based in Berlin and Potsdam.

The Difference between Hardware and Software Startups

Hardware is expensive to build, complex to produce and has to be perfect from the beginning. Additionally, hardware is often merely a Trojan Horse to sell software. Software, by contrast, is boring, abstract and has to endure more intense competition. An article about the differences between hardware and software startups.

A few days ago I gave a podcast entitled “Why Hardware Is More Complex Than Software”. Click here to listen to it (podcast in German). I subsequently promised people I would write about it in more detail. I will describe the differences in products, teams, business models, sales, operations and funding.

Hardware Has to Be Faultless – Software Can Have Bugs

The difference between hardware and software is easy. Hardware startups build physical products – software startups have virtual products. Furthermore, hardware companies have to build a complete 1.0 version and then decide whether to develop a new product (like iPhone 5 and iPhone 6) or improve on the existing one (like iPhone 5S). If the products don’t work properly, however, they could experience significant backlash from their customers.

Software startups have it easier. They can develop their products in iterations. They start with an alpha version, have private or open beta and then a public 1.0. Most software products are buggy; perfection looks different. Software can be constantly improved and developed. It is an ongoing process with releases.

Hardware Teams Are Bigger

It’s easy to start a software company. You need 2 developers and a part-time business guy. They should be able to cover front end, back end and machine learning. Don’t worry if you don’t have the business guy. Most SaaS teams make it pretty far without them. If you do e-commerce or online marketplaces, it is often the other way round. In such cases, it is common to have two ex-consultants who then hire a CTO to start.

For hardware companies, it is more difficult to put the team together. You need a product designer, a hardware engineer, two software developers (front end and back end) and a full-time businessman, since the processes are complex right from the beginning.

Hardware Companies Try to Sell Software

Business models for software companies are well known: e-commerce, online marketplaces, lead generation (advertising, affiliation), platforms, SaaS and APIs.

There are fewer ways to earn money with hardware.

Sure, you can always sell the hardware. However, you then have no customer lifetime relationship and no returning revenues. Everyone who once earned money with software and enjoyed MRR (monthly recurring revenue) struggles with this.

With hardware-as-a-service, you charge on a monthly or yearly basis, comparable to software-as-a-service (SaaS). Most often you rent your hardware to you customer and provide them with services on top. These can include analytics or access to cloud services.

Using hardware-enabled-services is an additional way to increase revenues. On top of selling the hardware, you can upsell with premium features. Fitbit takes a yearly fee if you wish to see more detailed statistics and data. If you want to store the videos of the surveillance camera Canary, it costs extra. It also costs more if you wish to have 3G mobile Internet access for independence from WiFi.

The final business model is hardware-as-a-platform. In this case you sell software, effectively using your hardware as a Trojan Horse to do so. The hardware is merely the access point to an app store where users spend their money. Take Oculus Rift. First you buy the hardware and then you have access to their app store, where you can buy virtual reality applications. Facebook also has two revenue streams. Or consider the Amazon Kindle. Without buying eBooks, the hardware itself is useless.

Hardware Companies Make Money before They Produce

One of the few advantages of hardware companies is in sales. Hardware startups can use the existing infrastructure of retailers, wholesalers and online marketplaces. It is also possible to pre-sell your product on Indiegogo and Kickstarter. Even if you don’t have a product yet, you can generate paid pre-orders.

Software is most often sold over marketplaces and platforms. This usually entails the use of social marketing, content marketing and performance marketing.

When a company is doing B2B (business-to-business) sales, there is no way around picking up the phone and cold calling customers.

Hardware Is Complex

 If you develop software, it’s easy to get it tested by your users. Either you have a demo server, use TestFlight for Apple apps or give people beta access. And once you are live, you can steer your company with KPIs (key performance indicators) like conversion rates, DAU (daily active users), churn, retention, CAC (customer acquisition costs), CLTV (customer lifetime value) and MRR (monthly returning revenues).

 Hardware, by contrast, is very complex. You start with a working prototype, usually no more than a shoebox with cables and an Arduino board. Then you start to 3D print your first casing. After months of developing, you start to source suppliers and look for producers. Once you have negotiated all the contracts, you get quotes and timings from the producers. You then have to worry about assembly and logistics.

Next you start your series-0 of the first ten to fifty produced parts. You have to pre-pay for tooling and start with testing. You will most likely realize that many parts of your product need redesigning. As a next step, you start with testing and grapple with inventory management, working capital, supply chain management, customs, taxes and local regulations.

Hardware Is Expensive

It is cheap to develop software at the beginning. At my former company, Wunsch-Brautkleid, we invested less than €1,000 to have an initial MVP (minimal viable product). Thanks to WordPress, GitHub and AWS, developing software is cheaper than never. However, speed is still of the utmost importance.

Software teams can find a product/market fit with less funding – usually between €100,000 and €300,000. Great teams often need even less.

Money is needed to improve on the product and for marketing purposes. The general rule is that more funding equals faster growth. Since it is often “winner takes all”, speed means survival.

It’s easy for a software company to collect money. Everyone is investing in digital.

For hardware companies, however, things are tougher. The first prototype may well be simple (less than €100 for some boards, cables and sensors), but to test a product/market fit, you have to produce and sell something. For that you need at least €500,000. Most teams burn between €2m and €5m before ever delivering their first physical product to customers.

A further hurdle to overcome is the fact that without money, you can’t build stock. Without money, no suppliers or producers will work for you. If you wish to grow, you have to finance your sales before generating any cash.

There are a few groups, however, who do finance and support startups. To name them: HAX, Hardware Club and Bolt.

 Why Should I Start with Hardware?

Hardware is expensive, difficult and complex. There are good reasons many avoid it. Why should you start a hardware company? For starters, you reach customers you won’t reach with software. There are plenty of opportunities to earn money with hardware. Hardware is exciting. People love hardware. On the flip side, software is subjected to more pressure through tougher competition. The slow ones lose.

 Ultimately, the choice is based on how you would rather spend your lifetime.

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