German AI Startup Landscape (2022)
The fifth annual AI Startup Landscape

appliedAI publishes the annual “German AI Startup Landscape” to highlight AI startups in Germany, promote the use of AI and create more opportunities for partnerships between startups and companies. Together with our more than 40 partners from academia, government and industry, we want to create an ecosystem in which AI startups can thrive and help shape the future of AI for the benefit of society. Our central database of high-quality AI start-ups gives corporations and SMEs easier access to AI partners they can trust. The data collected this year shows that the AI scene in this country is maturing and that well-known start-ups are increasingly establishing themselves on the market.

Together with NVIDIA, Google and nine venture capital firms (Digital+ Partner, Earlybird Kapital, eCAPITAL, High-Tech Gründerfonds, HV Holtzbrinck Ventures, Lakestar, UVC, La Famiglia and Asgard), we examined more than 1,000 start-ups (see below for details on the methodology). All start-ups were founded after 2011 and have a business model based on machine learning. The start-ups were founded in Germany or conduct their main business activities in Germany.

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Download the high-resolution overview of the AI Startup Landscape 2022 here: 

Methodology

The AI start-ups included in the landscape are private companies founded after 2009 that have their headquarters or central development activities in Germany. They focus on machine learning (ML) or make significant use of ML. The selection process can be summarised as follows:

• The start-ups are compiled from various public (e.g. Crunchbase, LinkedIn) and private (VC network) sources to create a comprehensive long list.
• Die Start-ups werden anhand von Daten, Talenten, KI-Methoden, Skalierbarkeit und Gesamtqualität bewertet und anschließend geclustert (siehe Logik für das Clustering).
• Die Start-ups werden zunächst von unseren KI-Ingenieuren und -Strategen bewertet („valide“, „aufsteigend“, „Longlist“ und „verworfen“), um eine Shortlist zu erstellen.
• Die Shortlist wird von unseren Mitwirkenden (Jury, bestehend aus Digital+ Partners, Earlybird Capital, eCAPITAL, Google, High-Tech Gründerfonds, HV Holtzbrinck Ventures, Lakestar, NVIDIA, Speedinvest und Unternehmertum Venture Capital Partners) unabhängig bewertet und beurteilt. Die Rückmeldungen werden synthetisiert und das Endergebnis wird visualisiert.

Clustering-Logik

The logic for clustering is based on Shivon Zilis' Landscape for Machine Intelligence. It is developed from the perspective of companies that want to use AI in their business:

• Enterprise Functions: Increase the productivity of existing tasks – support your employees with ready-to-use, AI-enabled tools that make their daily work easier and thus increase productivity.
• Enterprise Intelligence: Leverage new data sources – unlock new insights that were previously too difficult or too expensive to obtain using traditional methods.
• Technology Type: Build products with ML – give developers the tools they need to create and use machine learning software and gain a competitive advantage.
• Industries: Use AI-first products – leverage and collaborate with start-ups that offer industry-specific products and services using machine learning.

Growth Landscape 2022

 

Facts and figures

• There are 304 start-ups on the map for 2022, representing a growth rate of 9%. The decline in the growth rate is due to a change in methodology and the creation of a comprehensive list in 2021.
• Of the 304 start-ups, 228 remained on the list from the previous year and 76 start-ups were newly added.
• Of the 50 companies that are no longer on the list, 32% have been acquired, 20% are in liquidation, 4% have moved away from using AI in their product, 2% have gone public, and the remaining 40% were founded more than 10 years ago.

Location

Facts and figures

Overall, the concentration of start-ups in Berlin and Munich fell from 64% to 57%. Twelve new cities are represented on the 2022 map that were not included in 2021. These are:

• Bad Reichenhall
• Heidelberg
• Bad Schwartau
• Konstanz
• Lahr
• Leinfelden-Echterdingen
• Luneburg
• Osnabrück
• Schönenberg-Kübelberg
• Triberg im Schwarzwald
• Wolfratshausen

Bavaria has closed the gap and now has only 13% fewer start-ups than Berlin, compared to 35% last year. 70% of Bavarian start-ups are located in Munich.

Funding

Facts and figures

• Start-ups founded in 2014 or later received the most funding per company.
• Most funding goes to B2B AI start-ups, accounting for 88% of the total.

• The start-ups receiving the most funding are located in Saxony, followed by Bavaria and Brandenburg. Berlin's start-ups receive only a modest amount of funding.

Sector

Facts and figures

• The majority of companies focus on the needs of a specific industry, while only 14% are working on developing an AI tech stack.
• The most attractive industries for AI start-ups appear to be healthcare, manufacturing and transport.
• If a start-up decides to focus on a specific business function, the emphasis tends to be on customer service and marketing.
• Computational linguistics and computer vision are the most popular business intelligences that German AI start-ups focus on.
• In terms of the AI tech stack, the main development is taking place in AI applications and platforms.

Contributors

Rights & permission to use

We consider it our duty to pass on this information. Feel free to use this landscape as part of a presentation, lecture or project. This is permitted and encouraged, as long as you always use the visual representation and refer to us accordingly. If you change anything in our landscape, you must mark this as your own modification. The content of this landscape is published under the CC-BY 4.0 licence.