About Us
neurocat was founded in 2017 with a unifying desire to learn, grow, and provide exemplary services. We are focused on enabling companies to build the AI systems of tomorrow even while keeping people safe and maintaining values and ethics. We are joined in our mission by a multidisciplinary team consisting of research, industry, and application experts with a common desire of bringing robust AI systems to the public domain.
Our Vision
AI is changing the world. We unleash its full potential by making it safe and secure.
Our Mission
We empower ML pioneers in building mission-critical AI systems. We identify and mitigate AI risks through our cloud platform aidkit.
News
Neurocat accepted onto NVIDIA AI Inception program
Neurocat has been accepted into the NVIDIA AI Inception program! Being recognized by one of the giants in AI space showcases the potential of our software offering aidkit and neurocat's work in the domain of AI robustness, explainability and functionality. Want to try...
Papercat Thursday 12/11/2020
Proud to present the research paper contributed by colleagues at neurocat GmbH & Volkswagen AG. Risk Assessment for ML models is of paramount importance to understand the failure modes and improve the models before deployment. Our paper defines the standardized...
1E9 Interview Tarek R. Besold
Making AI models robust against adversarial attacks, unboxing the black-box models to make their decision-making process more explainable, and also working with standardization agencies to bring quality in AI to the forefront. It's all in a day's work for us. Read the...
Most Promising German AI Startups
Neurocat was voted one of the 247 most promising German AI startups by the initiative for applied artificial intelligence. We are pleased to be part of the AI Startup Landscape 2020 and working hard to shape the future of AI quality. The Startup Landscape and a...
Decision Boundary
State-of-the-art neural networks are vulnerable to adversarial examples. This major problem for the safe deployment of ML models arises when minor input modifications push a data point across the decision boundary of the model. The existence of adversarial examples is...
Times of Growth
Since the beginning of 2019, neurocat’s manpower has more than doubled. With all teams growing fast, we significantly expanded our office space. Luckily, we were able to move into a second floor in our company headquarter in Adlershof. This is just the beginning: If...
Techcode Pitch Won
The world's leading trade show for industrial technology and AI: Hannover Messe, Germany. With 6,500 exhibitors and over 250,000 visitors, it’s the place where digital innovations meet industry heavyweights. When Chancellor Angela Merkel opened Hannover Messe on 1...
Robustness Verification: Seminar Presentation at HU Berlin
Two of our cats are soon going to give a talk about the current status of duality-based adversarial robustness verification. The content will strongly rely on the recent publication ”Training Verified Learners with Learned Verifiers” by K. Dvijotham et al. (DeepMind)....
Interview Adlershof-Journal
What is growth? The Adlershof Journal examined beliefs about growth and interviewed us about AI security and our personal growth story. After a conversation with editor Peter Trechow, our way to grow, successes and ambitions were printed in the September/October issue...
Website launched
After a year of hard and exciting work the time has come for a first small website! Today we launched the first version of the site and plan to fill it with more and more content in the next few weeks. Our loyal fans will know what we mean when our website was...
Wasserstein Verification Paper Published
We are proud to present our joint work with the University of Göttingen. Formal verification of neural networks is a challenging topic! In the past, verification methods were mainly focused on Lp-norms for measuring imperceptibility. Using Lp-norms for measuring the...
Neurocat accepted onto NVIDIA AI Inception program
Neurocat has been accepted into the NVIDIA AI Inception program! Being recognized by one of the giants in AI space showcases the potential of our software offering aidkit and neurocat's work in the domain of AI robustness, explainability and functionality. Want to try...
Papercat Thursday 12/11/2020
Proud to present the research paper contributed by colleagues at neurocat GmbH & Volkswagen AG. Risk Assessment for ML models is of paramount importance to understand the failure modes and improve the models before deployment. Our paper defines the standardized...
1E9 Interview Tarek R. Besold
Making AI models robust against adversarial attacks, unboxing the black-box models to make their decision-making process more explainable, and also working with standardization agencies to bring quality in AI to the forefront. It's all in a day's work for us. Read the...
Most Promising German AI Startups
Neurocat was voted one of the 247 most promising German AI startups by the initiative for applied artificial intelligence. We are pleased to be part of the AI Startup Landscape 2020 and working hard to shape the future of AI quality. The Startup Landscape and a...
Decision Boundary
State-of-the-art neural networks are vulnerable to adversarial examples. This major problem for the safe deployment of ML models arises when minor input modifications push a data point across the decision boundary of the model. The existence of adversarial examples is...
Times of Growth
Since the beginning of 2019, neurocat’s manpower has more than doubled. With all teams growing fast, we significantly expanded our office space. Luckily, we were able to move into a second floor in our company headquarter in Adlershof. This is just the beginning: If...
Techcode Pitch Won
The world's leading trade show for industrial technology and AI: Hannover Messe, Germany. With 6,500 exhibitors and over 250,000 visitors, it’s the place where digital innovations meet industry heavyweights. When Chancellor Angela Merkel opened Hannover Messe on 1...
Robustness Verification: Seminar Presentation at HU Berlin
Two of our cats are soon going to give a talk about the current status of duality-based adversarial robustness verification. The content will strongly rely on the recent publication ”Training Verified Learners with Learned Verifiers” by K. Dvijotham et al. (DeepMind)....
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Germany’s most modern and advanced science and technology park!
neurocat GmbH
Rudower Chaussee 29
12489 Berlin
Germany
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