The Sixth Annual AI Startup Landscape
In order to highlight the AI startup landscape in Germany, drive AI adoption and create more partnership opportunities between startups and corporations to enhance the overall knowledge on applied AI, every year the appliedAI Institute for Europe publishes the German AI Startup Landscape - Germany’s most important and detailed analysis of the AI Startup scene.
Together with the help of our partners from academia, government and industry, we have set out to create an ecosystem in which AI startups can flourish to help shape the future of AI for the benefit of society. By creating a centralised database of high-quality and externally validated AI startups, we provide easy access to enable connections between corporations and SMEs as well as governmental institutions to AI partners they can trust. For the first time, this year we are also introducing a list of the most highlighted 20 AI Startups in Germany.
Together with NVIDIA, Intel and twelve renowned venture capital firms (Cherry Ventures, Earlybird Capital, UVC Partners, Yttrium, Lakestar, High-Tech Gründerfonds, eCAPITAL, La Famiglia, Asgard, Burda Principal Investments, HV Capital, and Born2Grow), over 1000 startups were examined. All startups were founded in or after 2013 with a primary business model based on AI (cf. details on methodology below). All AI startups featured were founded and are headquartered in Germany.
By the way: We are now taking applications for the AI Startup Landscape 2024 - so if you’re a hot AI Startup and want to be featured on next year’s landscape, feel free to apply!
Download the high-resolution version of the landscape
Methodology
Following academic standards, we developed a robust, strict and objective methodology for screening, analysing and evaluating all AI Startups in Germany. Overall, the process can be summarised as follows:
During the year, startups apply to be featured on the Landscape via our online survey. Moreover, we screened the entire German Startup Landscape and accepted nominations from our contributors (NVIDIA, Intel, Cherry Ventures, Earlybird Capital, UVC Partners, Yttrium, Lakestar, High-Tech Gründerfonds, eCAPITAL, La Famiglia, Asgard, Burda Principal Investments, HV Capital, and Born2Grow).
Startups are then evaluated based on data, talent, AI methods, scalability, overall quality and subsequently clustered (see “clustering logic” below).The startups are initially rated (‘shortlisted’ or ‘discarded’) by our AI Analysts to create a shortlist. To enhance the validity of our results, all startups are evaluated by several experts and the inter-rater reliability is calculated. Unclear cases - i.e. startups evaluations with a low interrater reliability - were then individually evaluated in a larger expert group, resulting in a final “shortlist” or “discard” decision.
Startups from the AI Startup Landscape of the previous year are automatically transferred to the new year iteration unless they have closed their business, were acquired, pivot their business model away from AI or moved to a different geographical location. If a startup was on the previous year iteration but is now older than 10 years, it was also deleted.
In order for a startup to be approved for the AI Startup Landscape, they must meet the following requirements:
- Be a registered company.
- Have been founded less than 10 years ago or pivoted their core business model to AI less than 10 years ago (including 2013).
- The startup’s headquarter must be situated in Germany.
- They should have a minimum of two Full Time Equivalents (FTEs)
- They should have a minimum of one FTE with AI competence
- They should have AI at their core or exhibit a significant usage of AI.
- The start-up respectively its business model has a high face validity (e.g., professional website, convincing business model, etc.).
The shortlist is independently evaluated and rated by our jury (NVIDIA, Intel, Cherry Ventures, Earlybird Capital, UVC Partners, Yttrium, Lakestar, High-Tech Gründerfonds, eCAPITAL, La Famiglia, Asgard, Burda Principal Investments, HV Capital, and Born2Grow).
In a final step, all feedback received is then synthesised and analysed by the experts of the appliedAI Institute for Europe.
Clustering logic
The clustering logic is based on Shivon Zilis’ landscape of machine intelligence. It is developed from the point-of-view of companies that want to use AI in their businesses:
- Enterprise Functions: Increasing productivity of existing tasks. Support your employees with ready-to-use, AI-enabled tools supporting their day-to-day work to increase productivity.
- Enterprise Intelligence: Exploiting new data sources. Tap into new insights that were previously too difficult or expensive to be gained through conventional methods.
- Technology Type: Building products with ML. Give developers the tools that they need to build and leverage machine learning software to gain a competitive advantage.
- Industries: Leveraging AI-first products: Use and cooperate with startups using machine learning to offer industry-related products and services.
Landscape Growth
A massive surge in the number of AI Startups based in Germany has taken place. There are 508 startups on the German AI Startup Landscape 2023 representing a tremendous 67% growth compared to the previous year. From 304 AI startups on the 2022 landscape, 262 remain on the list and 246 new AI startups were added to the list. Out of 42 AI startups that are not represented on the German AI Startup Landscape 2023 anymore, 28% were acquired, 38% are in liquidation, 10% had shifted the product or the company and 24% had to be removed as they were now older than 10 years. Thus, the survival rate of AI Startups is extremely high compared to the survival rate of non-AI Startups.
Overall, we believe that the massive surge in the number of AI Startups mainly stems from two reasons: First, it needs to be noted that there is a discrepancy between the actual founding of an AI Startup and being featured on the AI Startup Landscape. The reason herefore is that only AI Startups are listed that display a strong business model with a certain number of FTE (cf. sub-section “Methodology” for further information). As such, there is a time lag between the initial founding of an AI Startup and being featured in our list, as only highly promising startups are listed (and, in turn, AI startups with limited resources and unspecified value propositions are not yet listed as they are still in the progress of further development). Secondly, we advanced our methodology and expanded our data collection process. Thus, to some extent the underlying reasons for the high growth figure might also be attributed not only to the rapid expansion of the German AI Startup Scene but also to an improved data collection process.
Location
As in the last editions, the cities of Berlin and Munich continue their domination in the AI Startup Landscape. The share of two cities amounts up to 52% of German AI startups. This year, Berlin again clearly dominates as the German city with the largest number of AI startups (165), while Munich ranks in second place (99 respectively 108 including the suburbs of Munich). However, other cities are catching up, with the following cities reaching a two-digit number of AI Startups: Hamburg (41), Darmstadt (17), Karlsruhe (17), and Cologne (15).
On a federal state level, Berlin (32,5%) again clearly dominates the AI Landscape in Germany, followed by Bavaria (24,6%), North Rhine-Westphalia (10,2%) and Baden-Württemberg (9,6%).
To establish a more meaningful interpretation of the results, the AI Startups per capita of a federal state should be considered. This leads to an interesting shift in the ranking. Specifically, while Berlin as a city state ranks first place again, it is followed by Hamburg, Bavaria, Hesse, Baden-Württemberg, and Saarland. The numbers highlight that there is a significant disparity between the federal states in Germany, with Berlin having approximately 100x more AI Startups than Saxony-Anhalt on a per capita basis.
Funding
Approximately half of the AI Startups listed in the AI Startup Landscape 2023 received a significant amount of funding (subject to publicly available information). For the AI Startups funded, the average amount of funding received is 14,8 million USD, whereas the median is 5,4 million USD. Averaged for founding years, the amount of funding received increases over time, as older startups prove to be successfully established in the market and unsuccessful startups are typically liquified after not being financially successful.
Notably, 81 AI startups received funding larger than 10 million USD. Moreover, 119 AI startups received funding between 1 and 10 million USD.
Industry sector and enterprise functions
For the AI Startup with an industrial focus, this year we observe a dominance of AI startups in the following German key industrial sectors: (1) Human health and social work activities, (2) manufacturing, and (3) transportation, mobility, & storage.
The following figure shows the distribution of AI Startups among industries (please note that only industries with at least 10 active AI Startups are included in this figure).
On the Enterprise Function front, German AI startups are very active in the areas of Production (30), Research & Development (27), Operations (24), Marketing (19), and Customer Service & Support (18).
Moreover, it is notable that almost all AI Startups analysed are B2B-Startups. Indeed, less than 5% of the AI Startups are active in the fields of B2C or B2G.
Technology Type and Enterprise Intelligence
Regarding the technology type that German AI Startups tend to be active in, it is noticeable that only very few AI Startups build frameworks (11) or infrastructure (10) - fields where typically a high revenue can be created from.
When it comes to the underlying enterprise intelligence, German AI Startups are very strong especially in the fields of computer vision (28%) and natural language processing (25,3%). Moreover, AI Startups are active in forecasting (15,1%) and planning (11,6%), and discovery (8%). Surprisingly, only 5,8% of the AI Startups analysed are predominantly active in the field of robotics - a branch of engineering that historically is extremely important for the German industry.
Highlighted AI Startups in Germany
For the first time, this year we are also introducing a list of 20 highlighted AI Startups in Germany. This list was compiled based on a voting of the jury (i.e. NVIDIA, Intel, Cherry Ventures, Earlybird Capital, UVC Partners, Yttrium, Lakestar, High-Tech Gründerfonds, eCAPITAL, La Famiglia, Asgard, Burda Principal Investments, HV Capital, and Born2Grow), where each contributor was allowed to nominate the Top AI Startups. The final list was subsequently consolidated and ranked by the AI experts of the appliedAI Institute for Europe. The appliedAI Institute for Europe did not participate in the voting itself.
Based on the objective jury voting, the following startups were selected as being the most highlighted AI Startups in Germany for 2023 (please note that the order presented is alphabetically and non-hierarchical):
- Aleph Alpha
- askUI
- Brighter AI
- Celus
- Deepset
- Frequenz
- Helsing
- HQS Quantum Simulations
- Hyperganic
- Luminovo
- Navvis
- Parloa
- Paretos
- Qdrant
- Scoutbee
- SPREAD
- Taktile
- Twaice
- Ultimate.ai
- ZenML
Contributors
How you can use the AI Startup Landscape 2023
As a non-profit organisation, we believe that sharing this information is our obligation. Using this landscape as part of a presentation, talk, or project is allowed and encouraged as long as you always use the visual representation and reference us appropriately. Changes to the AI Startup Landscape 2023 have to be marked as your own changes. The content of this insight is published under CC-BY 4.0.
Kontaktinformation
We will be more than happy to discuss the insights of the AI Startup Landscape with you. If you have any questions or comments, please feel free to contact us:
Disclaimer
The data used in the AI Startup Landscape 2023 was collected and analysed to the best of our knowledge and understanding at the time of writing. While we strive to ensure the accuracy and reliability of the information presented, it is possible that errors, omissions, or inaccuracies may exist. Therefore, we cannot guarantee the completeness, correctness, or timeliness of the information provided.
The content provided is intended for general informational purposes only and should not be considered as professional or legal advice. Any reliance you place on the information is strictly at your own risk. We recommend verifying any critical information through additional sources or consulting with appropriate experts before making decisions or taking actions based on the provided information.