Merantix

Transforming the world with curious minds

We conceptualize, build, and scale AI ventures.

Merantix is a research lab and venture builder in the space of artificial intelligence. We help mid- to large-sized companies explore and leverage the potential of deep learning. We have a strong bias for partnerships with companies that have powerful data sets, and relatively short decision cycles. Consulting fees are not our main incentive. We are willing to take investment risks together with our venture partners.

We build partnerships with leading companies and organizations to assemble complex datasets and build machine learning solutions that address industries such as health, finance, automotive and advertising.

Icones How #3 Merantix (SHARED) 170228
Products

We iteratively transform models into standalone … [more]

Products

We iteratively transform models into standalone products. This means scaling and generalizing models, building stable APIs that support client needs, ensuring data security, and more!

Icones How #4 Merantix (SHARED) 170228
Machine Learning

Merantix develops models that predict actionable … [more]

Machine Learning

Merantix develops models that predict actionable insights. We use state of the art deep learning techniques and infrastructure while applying rigorous measures of success.

Icones How #2 Merantix (SHARED) 170228
Datasets

We build partnerships with leading companies … [more]

Datasets

We build partnerships with leading companies and organizations to assemble complex datasets. We target data science challenges that go beyond rule-based solutions or human capabilities.

Ventures

When products reach a certain maturity … [more]

Ventures

When products reach a certain maturity and critical mass of users, we spin off companies with dedicated teams.

Industries

We form joint venture partnerships in which we serve as an artificial intelligence laboratory and venture builder. We leverage our expertise in building machine learning infrastructure and applications and combine it with our partners’ datasets, their domain specific knowledge, and market access. We apply cutting edge research to real-world problems, conceptualize, build, and scale ventures that deliver unmatched value in many industries.

Close

Finance

The financial services industry has a long history of taking advantage of new technologies, and deep learning is no exception. Today’s financial institutions use artificial intelligence to improve prediction models, analyze cash demands and trading. Merantix provides cutting edge technology to support our venture partners in their effort to stay ahead of the curve.

High Frequency Trading

Merantix built an AI-based system capable of predicting currency exchange rates at market relevant speeds. Our deep neural networks recognize complex market movements way ahead of traditional methods. Through our partnership with an experienced HFT trading firm, we are able to deploy our models on the latest infrastructure, making sure that we can compete at the forefront of high frequency trading. We see the HFT arena as a great playground to test state-of-the-art deep learning research, as HFT is all about squeezing the last bit of performance out of prediction models.

Credit Scoring

In partnership with Intrum, Europe’s leading credit and collection agency, Merantix developed technology to significantly improve the distinction between good and bad payers. In comparison to current scoring methods, our deep learning algorithm was able to reduce the amount of rejected purchases by 20%-30% while the general risk of default remained unchanged. This may ultimately not only reduce the default rate and thus cost, but could also increase the number of positive decisions and thereby lead to additional revenue.

Key figures

Accuracy
30 %
We were able to reduce the amount of rejected purchases by 30%, while the general risk of default remained the same.
Data points considered per day
2 M
Our model evaluates more than 2 M times a day to find the optimal trading moment.
Close

Health

As more data about genetic preconditions, biological markers and lifestyle factors are created and linked to electronic health records, a new era of healthcare is on the horizon. Deep learning will be a driving technology pioneering new models in health and life sciences. Moreover, DL increases the accuracy and quality of diagnoses and clinical treatments in various areas and has the potential to drive precision medicine, as it is capable of handling vast amounts of data gathered from mobile devices, genomics, and medical health records.

Medical Imaging

Merantix is building an AI-backed service that performs automatic diagnoses of radiology images. To train our deep learning system, we extract gold standard labels from given natural language text reports. This is an ongoing task and is being repeated for different use cases (X-ray, CT, MRT, etc.) and can be applied for imagery of varying body parts. Our system improves efficiency and allows doctors to spend more time with their patients by automating and streamlining the labelling process.

Alzheimer's Early Screening

What if you could detect Alzheimer’s up to 6 years prior to its onset, using only an iPhone?

We helped ETH spin-off company Altoida develop and productize a methodology that is based on 8 years of longitudinal clinical studies with more than 2700 Alzheimer’s Disease (AD) patients. After taking a 10-minute test on our iPhone app, Altoida is able to to tell you if you will develop AD within 6 years with an accuracy of 94%.

Patient Data

Merantix provides an efficient and automated approach to the analysis of large amounts of patient data. Using blood test data, urine samples and other accessible medical records our machine learning engine is able to support physicians in the detection, treatment and surveillance of a variety of conditions.

Key figures

Accuracy
94 %
Altoida's technology can diagnose Alzheimer’s disease up to 6 years prior to onset with 94% accuracy.
Medical Lab Tests
200 M
We work with a data set of more than 200 M medical lab tests.
Accuracy
98 %
We can automatically structure medical reports with more than 98% accuracy.
Close

Automotive

There have been massive improvements in autonomous driving, and other related capabilities in the automotive industry in recent years. Driven by the pioneers in the industry, full market adoption of these technologies is approaching quickly. Deep learning is a major enabler in the space of autonomous driving systems and is used for various tasks including the detection of other vehicles, classification of traffic signs and obstacle recognition. For machine drivers to become safer than human drivers however, there is still some way to go. Experts agree nonetheless that deep learning will take this hurdle in the coming years.

Feature Visualization

In partnership with Bosch, Merantix is working on evaluating and improving deep learning tools in autonomous driving. We are creating, training and evaluating neural nets that recognize objects, such as traffic lights, signs and cars, from driver-assistance system sensor data (i.e. videos and images). Our system visualizes the characteristics of a trained neural network based on state of the art research. Besides visualizing the parametrization of the neural network itself, the tool is also able to highlight relevant regions of an image, which triggered decisions by the neural network and quantify those.

Find below our open-source project:

Picasso: A free open-source visualizer for Convolutional Neural Networks

Key figures

Number of Papers
4
published in top-tier journals and conferences on visualizing neural networks.
Exposed Software
75%
of automakers do not have a hacking countermeasure strategy in place.
Growth Rate
10x
faster growth rate of the connected car market vs. the total car market.
Close

Advertising

Recently deep learning has entered the creative space and sparked surprise by producing music and impressionist style paintings. Until now, technology was often used to support humans in their artistry, soon however we will see more and more songs, paintings and performances entirely created by machines. Online advertising provides an ideal environment for AI-based systems to enter the creative space, as the success of the creative work can be quantified through engagement.

Creation Automation

The long term vision of this Merantix project is to fully automate the creative generation while improving conversion for marketers. Our model, developed in collaboration with Rocket Internet, analyzes designed creatives and predicts their performance by detecting recurring patterns in image data. We envision that this model will help us to automatically generate creatives in the future.

Key figures

Impact of creative on performance
30%
Estimations say that around 30% of the performance of an advertisement depends on the creative.
Number of creatives
1 M
We train our models on more than 1 M creatives to really understand what makes a creative stand out.

Maurice Burger

Maurice is a Business Developer at Merantix. He graduated Magna Cum Laude from Babson College where he studied Entrepreneurship and Economics. Before joining Merantix, Maurice worked for two of the largest global apparel corporations and co-founded a wearable technology company.

Adrian Locher

Adrian is a serial technology entrepreneur and founder of Merantix. He built and scaled his last business to a leading e-commerce player with more than 100M revenue and 200 employees. Adrian graduated from University of St. Gallen (HSG) with degrees in Business and Economics.

Ryan Holmdahl

Ryan is a Machine Intelligence Engineer at Merantix and is studying computer science at Stanford University. Prior to joining us Ryan worked for Microsoft and started his own health-tech company.

Rasmus Rothe

Rasmus is one of Europe’s leading experts in deep learning and founder of Merantix. He studied at ETH Zurich, Oxford, and Princeton. Previously he launched howhot.io as part of his PhD research, started Europe’s largest hackathon HackZurich, and worked for Google and BCG.

Josh Chen

Josh is a Machine Intelligence Engineer at Merantix. He graduated from Princeton with summa cum laude. Prior to joining Merantix, he worked in machine learning positions at D.E. Shaw & Company and Amazon.

John McSpedon

John is a Machine Intelligence Engineer at Merantix. Prior to working for Facebook and Sift Science, he completed his studies in Computer Science at Princeton University.

Ryan Henderson

Ryan is a Machine Intelligence Engineer at Merantix and holds a PhD in Chemistry from Cornell University. Prior to joining Merantix, he worked for Intel and a Berlin-based Blockchain company.

Luc van Gool

Prof. Luc van Gool is an advisor to Merantix. He leads the Computer Vision Lab at ETH Zurich in Switzerland and the Institute VISICS at the University of Leuven in Belgium. He has been the advisor to more than 10 computer vision startups and serves on the board of various top tier journals and conferences.

Radu Timofte

Radu Timofte is an advisor to Merantix. He is a Research Group Leader at the Computer Vision Lab at ETH Zurich in Switzerland. He has published many high-impact papers on Computer Vision and Deep/Machine Learning in top-tier journals and conferences.

Arne Bleckwenn

Arne is a Partner at Merantix. He is a serial entrepreneur and angel investor. After building and exiting an online gaming company, he has built AirBnB competitor Wimdu and raised 90M EUR venture capital. He graduated from WHU with an MBA prior to joining McKinsey.

Jonas Muff

Jonas is Head of Business Development at Merantix. He graduated with a Bachelor’s degree from the University of St. Gallen (HSG). During his studies he was CEO of the START Summit, a student-led entrepreneurship conference with over 1000 participants. Jonas is also the initiator of the START Fund (part of HSG Foundation).

Stefan Bunk

Stefan is a Machine Intelligence Engineer at Merantix. After graduating with a Masters degree summa cum laude from Hasso Plattner Institute, he continued research at the institute before joining SAP and HERE (Audi, BMW, Mercedes).

Filippo Scopel

Filippo is a Machine Intelligence Engineer at Merantix. He holds a bachelor in technology and management from TU Munich and a master in banking and finance from the university of St. Gallen. Before joining us he worked for Ernst & Young, Julius Bear and most recently in a Machine Learning position for a Munich-based IIoT company.

Gergely Szűcs

Gelgery is a Machine Intelligence Engineer at Merantix. After completing his masters in mathematics at the University of Oxford, Gergely went on to pursue his PhD at Stanford University, where he is conducting research in Algebraic Topology.

Combining your industry expertise with our machine learning skills,

for a successful co-creation of new business opportunities.

Facts not just words

100 M €

Annual revenue of last venture

200 +

Peer-reviewed research papers

150 M

Images uploaded to howhot.io

2000 +

Hackers at our Hackathons

Your data and knowledge,

Schedule an appointment

Meet us
Merantix GmbH
Friedrichstraße 68
10117 Berlin, Germany
Registration No.
HRB 176845 B
USt-IdNr
DE307424335
Managing Director
Dr. Rasmus Rothe

We are growing,

we are looking for the most talented curious minds out there.

Career

Machine Intelligence Engineer

Berlin, Germany