The AppliedAI Institute for Europe publishes the German AI startup landscape every year. It is designed not only to improve general knowledge about applied AI, but also to draw more attention to German AI startups. This is intended to create more opportunities for partnerships between startups and enterprises and thus advance the use of AI.
The current seventh “German AI Startup Landscape” includes 687 startups, representing growth of 35 percent compared to the previous year. This places the growth rate significantly below the previous year’s 67 percent. Of the 508 AI startups on the 2023 AI landscape, 467 remain represented, with 220 new startups added this year. The reasons why 41 AI startups did not make the list are varied: 49 percent have relocated their headquarters abroad, 17 percent were acquired, and ten percent are in liquidation. Additionally, 24 percent had to be removed because they exceeded the landscape’s age limit of ten years. Notably, almost all AI startups that relocated their headquarters abroad established their new headquarters in the USA.
Berlin, Munich and Hamburg at the top
As in previous versions of the “German AI Startup Landscape,” the cities of Berlin and Munich continue to dominate this year. The combined share of both stands at approximately 50 percent of German AI startups. Berlin has a total of 209 AI startups, while the Munich ecosystem can boast 136 of them. Third-place Hamburg has 65 AI startups. The next positions are followed by Karlsruhe (17 startups), Stuttgart (16), Cologne (16), Darmstadt (16), Aachen (11), Düsseldorf (11), and Frankfurt (10).
At the state level, Berlin also secures first place with a share of 30.4 percent of all AI startups. This is followed by Bavaria (23.3 percent), Baden-Württemberg (11.5 percent), North Rhine-Westphalia (10.2 percent), and Hamburg (9.6 percent). When measuring the number of AI startups per capita, Hamburg as a city-state moves up to second place behind Berlin. Third place goes to Bavaria, followed by Saarland, Baden-Württemberg, and Hesse.
The “German AI Startup Landscape” categorizes startups into four clusters: Industry, Technology Type, Enterprise Intelligence, and Enterprise Function. Within these clusters, startups are further divided into subcategories covering a wide range of AI applications, from computer vision and robotics to human resources and sales, as well as manufacturing and infrastructure. The study also shows that one in five AI startups is active in the area of generative AI.
Funding of AI startups
Regarding funding, the landscape notes that approximately 38 percent of the listed startups (246 startups) were able to raise more than one million dollars. For them, the average funding amount is 17.1 million dollars, while the median is 5.5 million dollars. 80 AI startups even received funding of more than 10 million dollars.
Investment activities in newly founded AI startups have declined since 2021: While companies founded in 2021 have received a total of approximately 535 million dollars to date, AI startups founded in 2022 and 2023 together received only about 93 million dollars. While more mature AI startups typically attract higher funding rounds, it appears to be a challenge for younger founders who started in 2022 or later to raise capital.
The most promising AI startups in Germany
In addition to statistical data on the German AI landscape, a jury composed of landscape partners (Deutsche Telekom, NVIDIA, Intel, UnternehmerTUM, Cherry Ventures, Earlybird Capital, UVC Partners, Yttrium, HTGF, eCAPITAL, Burda Principal Investments, HV Capital, D11Z.Ventures, MIG Capital and AI.FUND) in collaboration with AI experts from the AppliedAI Institute for Europe has compiled a list of the most promising AI startups in Germany for 2024. Among the 27 selected startups are eleven teams from Munich.
Celus is working to make it possible for anyone to develop electronics at the push of a button. The startup’s AI selects suitable components and creates circuit diagrams and PCB layouts that are ready for production immediately. Just as code generators and compilers revolutionized software development decades ago, Celus brings these advantages and principles to the world of electronics.
Certivity empowers companies to understand and apply regulations to develop compliant products. To do this, the startup’s solution is integrated into the development process to seamlessly connect the legal and regulatory world with the technical domain. In this way, the startup automates the technical compliance process.
Dstack is an open-source container orchestration engine specifically designed for running AI workloads in any cloud or data center. It simplifies the fine-tuning and deployment of AI, integrates seamlessly into the open-source ecosystem, and leverages various hardware and cloud providers.
Fernride develops scalable automation solutions for trucks in yard and port logistics. The startup relies on the so-called human-assisted-autonomy approach, which enables remote operation of autonomous, electric trucks and combines them with autonomous driving technology on a scalable platform.
Floy aims to promote patient wellbeing through innovative technologies in radiology. To do this, the startup is committed to more precise diagnoses and early detection of health risks by helping radiologists use its artificial intelligence to detect difficult-to-see abnormalities.
Helsing equips existing weapons systems with AI that analyzes information coming from onboard sensors. The company is committed to transparency and explainability and relies on “human in the loop.” This means that the AI does not determine military targets itself, but rather supports officers in analyzing the situation.
Orbem has developed an AI-powered digital technology that automatically analyzes and classifies biological samples. In this way, the startup aims to revolutionize food production to meet the needs of a growing population.
Ororatech is developing a global, satellite-based early warning system for forest fires. The data is evaluated onboard the satellites using AI, and detected events are transmitted in real time. This makes it possible to assess risks in advance and detect forest fires worldwide early at any time.
Remberg helps organizations manage and digitalize their processes in service and maintenance around their facilities, equipment, and more in one place. The startup uses a so-called “Extended-” or “Anything-Relationship-Management” (XRM), a further development of the “Customer-Relationship-Management” approach – but for the Internet of Things (IoT).
Tacto has developed an “operating system for the supply chain”: centralized management of supplier relationships for industrial mid-market companies. The AI-based software is intended to enable strategic supplier management, uncomplicated handling of compliance for ESG regulations, and efficient and sustainable material procurement at optimized terms.
Trail ML wants to enable trust and efficiency in ML development with its data science co-pilot. To do this, the solution offers, among other things, automated documentation and test suites to free up developer time and ensure AI governance.
