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Top-10 Artificial Intelligence Startups in Switzerland

There’s an old Swiss motto that says, “money may not make you happy, but it makes you rich.” And rich they are. With a population of just over 8 million and a geographic area of about 41,000 square kilometers (that’s about a third the size of Pennsylvania for all you muppets out there that don’t use the metric system) Switzerland is small but has the sixteenth highest GDP-per-capita in the world. The country is built on services and traditional industries like banking, insurance, pharmaceuticals, and precision instruments (with a notable history in watchmaking as well). If by now you’re starting to think that the Swiss are just a bunch of punctual, well-to-do people in tailored suits with the ability to instantly bore anyone to tears, well, you’re pretty much spot on.

Switzerland may not have a governmental AI strategy, but its private sector has been voted the most innovative in the world for seven years straight by a bunch of people who are smarter than we are. According to venture capital firm Asgard, Switzerland already boasts the highest number of AI companies per citizen. With a strong economy and strong research roots comes venture capital funding. We browsed Crunchbase to find the ten most funded AI startups grazing in Switzerland’s lush alpine pastures.

Name Application City Funding
(USD millions)
Sophia Genetics Healthcare Lausanne 140.0
Starmind Big Data Kusnacht 25.0
KNIME Big Data Zürich 21.5
Avrios Fleet Management Zürich 14.0
Gamaya AgTech Lausanne 7.6
Piavita Animal Healthcare Zürich 6.5
Envoy Big Data Schaffhausen 5.0
Advertima Marketing St. Gallen 5.0
High-Tech Bridge Application Security Geneva 4.3
Fastree3D Autonomous Vehicles Ecublens 3.8

 

Click for company websiteFounded in 2011, Lausanne startup Sophia Genetics has raised $140 million in funding (more than half of which came just days ago) to develop AI algorithms that use genomic data to improve diagnostics. The company’s platform helps diagnose conditions like cancer, cardiac problems, and metabolic disorders, by detecting genomic variants associated with certain diseases. Sophia is also able to assess risks, diagnose patients, and also predict tumor evolution in oncology by combining medical images with biological and clinical data.

Sophia Genetics' AI algorithm differentiates between therapies based on genomic data

Sophia Genetics’ AI algorithm differentiates between therapies based on genomic data. Credit: Sophia Genetics

The process helps clinicians in choosing the right therapeutic strategy for each patient, a process that is usually complex and iterative. The platform can also help the development of new therapies by supporting clinical trials based on genomic information. The platform is used by 850 hospitals in 77 countries worldwide, and we’ll look to do a feature article on Sophia Genetics in the next few weeks so stay tuned.

Click for company websiteFounded in 2010, Kusnacht startup Starmind has raised $25 million to develop a platform for corporate knowledge sharing which is based on neuroscientific principles and powered by machine learning. First, Starmind connects all existing data sources at a community or company including Microsoft Office, Slack, the corporate intranet, and the like. Then, the app maps out interactions and builds an interactive knowledge base out of them, identifying certain employees as experts in their given fields.

Starmind's knowledge sharing AI in action

Credit: igloosoftware.com

Questions can be directed to these experts through a Q&A portal that, over time, unlocks the undocumented knowledge hidden in the organization’s talent pool. Testimonials say the tool has replaced email in many cases (we’ll believe it when we see it). Starmind is used by organizations like Accenture, Bayer, and Nestle.

Founded in 2008, Zürich startup KNIME has raised $21.5 million to develop an open source data science platform. The company’s analytics platform allows users to build data science workflows using simple drag and drop mechanics, choosing from over 2,000 pre-designed modules.

The KNIME data science tools allow drag-and-drop data and machine learning workflows

Credit: KNIME

Any kind of data can be used as an input, and the platform offers data manipulation tools (cleaning, validation, aggregation), along with support for machine learning models built in KNIME. The KNIME server allows team collaboration and automated workflow execution. The product suite comes with official extensions and integrations as well as open source community contributions like databases, text processing, and network relationship analysis making KNIME a full-service platform for data scientists. Sounds pretty similar to another tool we talked about in our article on Big Data vs. Data Warehouses. What’s the Difference?

Click for company websiteFounded in 2015, Zürich startup Avrios has raised $14 million to develop fleet management software powered by AI algorithms. The software covers vehicle procurement and registration, fleet data, costs, contracts, and damage management. Processes and documentation are automated as much as possible and fleet management is optimized from a financial perspective. Information on more than 8,000 suppliers is plugged into the system which allows for long-term planning of corporate mobility solutions, covering electric vehicles and car sharing options as well. Avrios provides a corporate car sharing app as a complimentary service, allowing companies to go green and go cheap. The company has more than 600 customers, mainly in Europe.

Click for websiteWe first looked at Gamaya’s agtech image analytics solution back in 2017 in an article titled 9 AgTech Startups Using AI to Grow Smarter. Founded in 2015, this Lausanne startup has raised $7.6 million in funding so far to develop a crop intelligence platform for farmers. Gamaya’s technology is built on hyperspectral imaging, a method of image capture covering a wide range of wavelengths instead of the three that the human eye can see. These hyperspectral images are collected from the air and space, combined with corresponding historical climate and weather records, and munched on by hungry machine learning algorithms that will find agronomic issues including nutrient deficiencies, diseases, as well as pest and weed infestations.

Gamaya's hyperspectral imaging combined with machine learning displays crop nutrient content among other factors

Credit: Gamaya

The output of the analysis is a set of targeted recommendations for optimum crop management and treatment. The company provides precision farming solutions for soybean growers and has also launched a solution geared towards Brazilian sugarcane growers. The company claims the data acquired from its cameras are 10 times more informative than any other monitoring solution currently on the market.

Click for company websiteFounded in 2016, Zürich startup Piavita has raised $6.5 million to develop a system that measures and analyzes the vital signs of horses using a palm-sized sensor attached to the animal’s body. The system gathers data continuously and provides diagnostics to veterinarians using AI.

The Piavita sensor for veterinarians mounted on the body of a horse

Credit: Piavita

As the sensor transfers data through a mobile connection, owners and vets can monitor horses during their daily routine over the long term which makes preventive medicine easier. The system also saves time for vets and allows them to provide more services on location instead of taking animals into a clinic for examination. The Piavita Vet System package costs $7,000 and the company is expanding in Europe at the moment with plans to enter the U.S. market as well.

Click for websiteFounded in 2015, Schaffhausen startup Envoy has raised $5 million to develop an application that combines contact data from social media, corporate address books, email, and CRM systems to summarize and visualize users’ personal networks. The app helps individuals and companies capitalize on these network assets by slicing and dicing the information across geographies, industries, and functions and uncovers previously unknown connections. Besides its corporate applications in sales, customer relationships, and recruiting, the tool can be useful in managing clubs, communities, and non-profit organizations as well. Basic access including network overview, analysis, filters and cleanup are free. The subscription-based Envoy Plus package adds the ability to combine networks across one or more organizations and collaborate in teams.

Click for websiteFounded in 2016, St. Gallen startup Advertima has raised $5 million to develop a system that interprets the appearance, motion, and behavior of people in real-time. With its use of computer vision and machine learning, Advertima can make screens, speakers, and light installations interact with the people around them based on their emotions, age, and gender.

Advertima's AI recognizes returning prospects and tailors signage to them.

Advertima’s AI recognizes returning prospects and tailors signage to them. Credit: Advertima

The service’s main benefits are in retail and banking with increasing customer loyalty, more footfalls, and better sales conversions. A retail use case includes the classification of the customer into the right customer segment and guiding him or her to the relevant parts of a store. The system also recognizes a returning customer and can show multi-screen stories to the prospect using digital signs.

We first covered Geneva startup High-Tech BridgeClick for company website in an article we wrote last year titled “AI for Web and Mobile App Security Testing“. Founded in 2007, the team has raised $4.3 million to develop an AI platform testing the security of web and mobile applications. Application Security Testing (AST) is an essential but not very rewarding task performed by security specialists (which is expensive) or developers (which takes them away from core activities). High-Tech Bridge has developed a human-in-the-loop machine learning algorithm that only requires human intervention when the algorithms aren’t 99% sure about something, and it learns from previous tests so less intervention is required over time. The company offers a “zero false-positive SLA” meaning every reported flaw is an actual security risk that needs to be addressed. The company also offers mobile app testing and trademark monitoring for free, using these educative products to grow brand awareness and acquire clients at the same time.

Click for company websiteFounded in 2013, Ecublens startup Fastree3D has raised $3.8 million to develop smart vision systems for autonomous vehicles and robots. Joining the nine startups developing LiDAR sensors we covered earlier, Fastree3D’s imaging sensors recognize and measure distances to fast moving objects in real-time for applications like driving assistance and autonomous navigation. The technology promises less false positives and false negatives than competing solutions, minimizes detection-reaction time by bringing the computational work into the sensor, and does all this using a cheap and reliable flash technique instead of constantly scanning the environment. Fastree3D’s system is used in autonomous vehicles and collaborative robots, and the company also provides hardware development toolkits for a limited number of partners wanting to develop additional applications to the technology.

Conclusion

Almost every time we write these, we get inundated with “you missed our sacred cow” emails. For all you Swiss AI startups out there who believe we missed them, please take time out of your exciting Swiss lives to go ahead and make sure Crunchbase is updated. We work from the information that is available on the Crunchbase database, but that doesn’t mean everything is up to date in their system. We’re always happy to write an article about your AI startup in exchange for top-shelf alcohol, watches, or just a plain old pile of Swiss Francs.

For the size of the country, there are some pretty exciting and well-funded Swiss startups that made our list, and we’re tempted to think there are plenty more where those came from. Seems like a national AI strategy is not necessarily a requirement to be a contender in the global AI race.

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