Thinking from the Human Perspective ... with the Possibilities of the Machine.
We combine methods from Design and Computational Thinking to create intuitive and innovative digital solutions for clients. From desktop and mobile applications, to algorithms and machine learning solutions.
Innovation Consulting
Product Vision
Advanced Data Science
Software Development
Strategic level
Operative level
Company perspective
Customer perspective
We support clients across four different areas and their combinations – reaching from the creation of early concepts to the implementation of tailored solutions.
Building upon many years of experience, we advise clients on a strategic level and create innovative solutions and product visions for internal and external projects. On an operational level, we create real value added by applying advanced analytics to business processes as well as promoting small and mid-size product developments through a strong partner network.
We are experts of the digital domain and help our clients benefit from the Digital Transformation.
We have learned that methods from design and computational thinking complement each other: the classical design process benefits from the stringency of data-driven computational thinking and can be used to improve networked and complex systems. And it is design that adds a human dimension to the process of computational thinking. The interplay of both – Design and Computational Thinking – constitutes our approach to shape a digital world.
We Explore Complex Problems and Uncharted Solutions.
We are experts of the digital domain and help our clients benefit from the Digital Transformation. Our motivation: to shape our future digital society.
The design process guides us by creativity and mutual inspiration. In order to understand problems and questions, we use methods from user–centered design. We talk to people, observe human behavior and evaluate findings based on our experience.
Through computational thinking we gain new insights. Quantitative research, data analysis and structured deep dives into the respective domains help us understand fundamental coherence and complexity within systems. We verify our hypotheses with the help of algorithms, models and simulations.
Lastly, we give a face to these new ideas and concepts. Every solution is different: Presentations, prototypes, apps, ... as well as podcasts and events. Through clear communication and great storytelling visions become tangible.
Digital / System / Trust
We are digital.
Digitalization enables connecting objects across different domains. In doing so products and services are transferred from the analog world to the digital one. They obtain a digital representation and thereby loose their physical limitations: In the digital space, objects can be freely multiplied, moved, changed and connected. New creative freedom arises which would have been conceptually unthinkable or technically impossible before.
We think systemically.
In the context of digitalization, products should be considered in a systemic way – meaning, in the context of their already existing and potential connections. As a result, the advantages of the digital space can be fully exploited and added value created. The digitalization is therefore essentially a systematization. It is about bringing together previously independent components (things, properties, processes, rules, ...) from different domains and letting them interact within new systems – to create novel solutions to old and new challenges.
We build trust.
The increasing level of interconnection between analog and digital objects also results in an increasing level of complexity of the associated systems. Users of digital products and services can no longer understand the underlying mechanisms. They have to trust in the respective product and service providers, which surprisingly many people are already doing today. In the future, it will be about maintaining that level of customer confidence through transparent and secure product and service design.
“Computational Thinking will be remembered as [...] the most important intellectual achievement of the 21st century.”
Art and science provide two different perspectives on the »Conditio humana« - on what it means to be human. The tension between them is constructive and reflects an open dialogue between rational thought and emotion, between head and gut. Similarly, Design and Computational Thinking offer different perspectives and tools.
AI-Powered
The fascination of creating digital products is strongly connected to the computational power of today's computers.
With their immense power to process large amounts of data in a short time, we have powerful tools and ways to design digital products.
Validation results from an automated neural net hyperparameter optimization
Algorithms are like a recipe for the computer to follow in order to achieve certain goals. These goals can be manyfold, like detecting a fire from gas data or using vital data for monitoring personal well-being and consumer health application. To develop these algorithms, there are two opposing approaches...
Bottom-Up Approach
Breaking down complex problems into their most basic and fundamental aspects – very often down to the physics – helps us understand the core principles of how a systems works (first principle thinking). Based on this understanding, we can explain how the signals in the data are formed and exactly how individual features in the data are to be interpreted (e.g. the specific aspects in the shape of an EV charging curve can tell you a lot about the battery health). Data analytics and algorithms can benefit from such fundamental understanding. Mathematical tools help us to extract useful information, that is hidden within the data.
Top-Down Approach
However, sometimes the mechanisms of cause and effect are very complex and it can be difficult to gain a basic understanding. A complementary approach, that is based on a large amount of labelled data, uses generic machine learning architectures (often called AI) that can be trained with such data. The system will then learn to mimic a certain intended behavior. Surprisingly even very complex behavior can be achieved with such an approach. The key to successful development of AI algorithms is to carefully train those algorithms in a way that they generalize very well, so their application in a product is robust and reliable.
We have multi-year, multi-domain and multi-project experience in collecting and curating relevant data, analyzing and understanding the data, and developing algorithms — using both bottom-up and top-down approaches.
Overheat and fire detection on multiple complexity levels.
In the case of our algorithm development for the Bosch Sensortec BME688 gas sensor we use both bottom-up and top-down approaches. We develop conventional algorithms for air monitoring and more complex machine learning approaches for specific fire detection.
Handling reliability was key to the development of these security related use cases:
Overheat protection for vans, campers and boats (based on conventional algorithms from temperature and humidity sensors).
Fire detection algorithms with an advanced threshold mechanism that can detect sudden changes in the air composition.
A detection for smouldering fires based on a neural network that would detect carbon monoxide at concentrations that are way below any danger for people.
12-dimensional neural net classification results projected into 3-dimensional space
It was important that we designed the user interface of BME AI-Studio in an intuitive way, so users can easily create and configure their own AI algorithms.
If you don't know what your customers can do with it, empower them to find out on their own.
Together with Bosch Sensortec we are investigating the possibilities of AI-driven gas sensors since 2019. And it turned out, there are simply too many interesting use-cases that can be explored. That's why we transferred our process and knowledge on how to explore gas sensor use cases into a software application, that lets customers build their own algorithms in a simple to use and easily accessible way. A challenge from both design and computational perspectives – harmonizing multiple years of gas sensor experience and various data science approaches into a coherent hardware/software ecosystem: BME AI-Studio.
We stripped down our complex machine learning pipeline in a way that even non data scientists can make use of it. Therefore, we needed to ...
... generalize and abstract the process of developing AI-based gas sensor algorithms, since initially we did not know which type of use cases would be relevant for users.
... find suitable presets and defaults that work well for the every type of use case.
Consumer health applications as a first step into fully digitized health care systems.
Providing widely available access for healthcare services through remote monitoring and automated data analytics is key for tomorrow's health care systems. The aging global population and rising healthcare costs necessitate efficient, accessible, and cost-effective healthcare solutions, which digital technologies can provide. Consumer health products are an important step, and in close collaboration with Bosch Sensortec, Universitätsklinikum Freiburg (Medical Center Freiburg), Saarland University and others, this is a constant effort at Intervall. In addition, the collected data and knowledge can later lead into medical grade products.
For example, monitoring and analyzing indoor air quality can have multiple benefits:
Bad air quality warnings connected with notifications for necessary venting, resulting in better living and working environments.
Analyzing the micro dynamics of indoor situations can provide useful information for the spread of viral infections. Humidity, temperature, activity tracking and the detection of specific volatile organic compounds can help estimate the lifetime and mobility of virus-containing aerosols and thus predicting the risk of viral infections.
Sleep tracking is another field, where we have been working for years now to detect and optimize parameters for a healthy night. Therefore we like to collaborate internationally in public funded projects.
With a built-in gas sensor, the smartphone can be used on the bedside table for AI-assisted sleep monitoring.
Distributed temperature, humidity and gas sensors within office buildings enable air quality monitoring for a better working environment.
Enriching people's lives through digital products is now enabled by the power of ubiquitous computing. At Intervall, we use algorithms based on first-principle understanding and AI-powered technology in a variety of areas, such as charging infrastructure, smart home, personal wellbeing and many more.
User Interfaces for Complexity
We live in a complex world. Technology is progressing at a breathtaking rate, business structures are becoming increasingly tangled, user needs are more individual than ever. At the same time, digital interfaces already form the main access point to large parts of our professional and private lives, and will do so even more in the coming decades.
At Intervall, we believe that designing these digital interfaces to our complex world is critical.
We create excellent digital user experiences and user interfaces — with a focus on making complex topics understandable, accessible and easy to use.
The user interface of BME AI-Studio assists customers in configuring the hardware, collecting and curating the recorded data as well as using that data to create use case specific algorithms for the BME688.
Making Machine Learning Accessible
Bridging the knowledge gap.
Everyone talks about machine learning, but only few understand it. The underlying mechanics are complex.
With BME AI-Studio, we have developed a software ecosystem (including documentation and video tutorials) for Bosch Sensortec, that makes machine learning accessible and manageable for all users.
Both advanced experts and absolute beginners in the field are guided through all relevant steps and can train and test their own neural networks for the BME688 gas sensor.
How we approached the overall concept for BME AI-Studio:
A strict nomenclature was the basis for the concept of the user interface – a computational method we like to use in most projects, inspired by object-oriented software development.
We collected and structured all the key components of a typical workflow, set up a clear definition and gave them a name. Building on this, we designed an information architecture along the individual process phases.
The result was an amazingly clear software structure. Users are guided through the entire process from data acquisition, data collection and curation to the creation and configuration of machine learning algorithms.
From low to high fidelity in an iterative process: scribbles lead to wireframes, which serve as a template for the final user interface design.
Digitalizing well-established B2B processes and customer relationships.
Complexity not only arises due to technical sophistication or mathematical abstraction, also terminology and processes that have been optimized for many years can be very complex for newcomers. Together with Aurubis and their Digital Innovation Lab, we focus on making business processes in the domain of metal recycling more transparent and easy to understand. With a fresh outside perspective and rigor thinking we can carefully restructure what has evolved for more than 150 years.
Within the Aurubis Business Partner Portal we do not only cope with complex and very specific terminology of business-relevant processes, but also with a wide variety of users and requirements.
We designed the user interface in a very clear and structured way. The information is organized within a stringent pattern – a mental model, that helps users navigate through different sections and information.
The concepts and designs are critically evaluated at each intermediate step and extensively tested with internal employees and users to ensure that the digital expansion of customer communication supports all processes and integrates seamlessly into existing workflows.
Consistent use of colors and typography help to communicate the information architecture, in that way the clear user interface helps Aurubis customers to keep track of their metal accounts.
“Thanks to Intervall's creative and structured way of working, Aurubis has succeeded in digitizing its customer relationships and taking them to a whole new level.”
Dr. Harald Kolbe, Head of Aurubis Digital Innovation Lab
How fast do electrons move?
While designing the digital user interface for MAHLE chargeBIG we wanted to communicate MAHLE's expertise in constructing technical solutions, while at the same time making the user experience practical, efficient and fun to use.
We created a minimalistic graphical UI design based on the corporate identity of MAHLE. The design was intended as a guiding star into a more digital future, conveyed through a playful and lightweight appearance, which is also reflected in the start-up idea of chargeBIG.
A screenflow is an essential tool in designing mobile app experiences, because due to the limited size of mobile phone screens the information and processes have to be divided onto multiple screens.
4 pixels/s
We also put special attention into designing the charging experience itself. Since users can not really experience what's going on, we wanted to visualize the process from a engineering perspective.
What is really happening when charging a car? Current is flowing along the cable, electrons are moving through the copper.
We created a charging animation which - like under a microscope - makes the current flow of electrons visually and haptically tangible through a visual and audio-haptic experience.
Electrons are depicted as moving dots – their speed is directly coupled to the average electron drift velocity in the copper cable at the respective charging power (100x faster for better visibility 😉).
Charging animation for AC charging speed
Charging animation for DC charging speed
From pioneering machine learning interfaces to streamlining century-old business processes, Intervall consistently transforms complexity into clarity and thus enriching user experiences across the digital landscape.
Envisioning Products
At first there is an idea – similar to a fragile little plant – it takes a lot of protection and courage to let it blossom by following and developing that idea into a product concept for something new. It is part of the creative process to be very careful and imaginative in the beginning, so new ideas can grow. Only if they do this will they have the strength to defend themselves against justified and important objections. These objections are also necessary to prevent us from going down all possible paths and focusing on the most important and promising ideas.
Patience and thoroughness are essential, as is understanding matters in depth, feeling your way forward, iterating and then courageously breaking new ground. We are thankful that our customers share our view and have trust in us. The basic groundwork will pay off later, and we can move forward much faster at a later stage if we have laid the foundations properly.
It is within the DNA of Intervall to take the first steps — to creatively form something new, where nothing has been before.
Sketching A modular showcase.
When we developed a new trade show exhibition for Bosch Sensortec for the CES 2022, we had only very little time to do so. Nevertheless we spent the time in developing a thorough concept, capturing all aspects that are necessary for the visitors to understand, before we went on to develop the concept and design. The result is a very modular showcase that is easily adaptable and extendable.
Making the trade show exhibit interactive with a mini lab environment for showcasing the AI functionalities of the BME688 at CES 2022 was key, so customers can understand the wide spectrum of possibilities.
A complete digital charging experience.
The fact that the foundations are so important is true for projects that need to be completed within a couple of weeks, as well as projects that turn out to be multiple year long runners. Like the project where we developed a novel digital ecosystem for EV charging.
Together with MAHLE chargeBIG, we developed and designed a complete digital charging experience.
A digital design system with a distinct visual identity for the MAHLE start-up
A mobile app that users can use to activate their charging point, monitor the charging process and also pay for it
A backend system that can handle communication with the users through the mobile app, but also with all charging points and a payment provider
An administration dashboard for chargeBIG clients to maintain their charging points, pricing, and charging sessions.
The chargeBIG software ecosystem presents itself to the end customer in a simple way: just a plug on the wall and a mobile app for all the rest. Plug and play!
No standard file format for gas sensor data? Let's invent one.
Sometimes, we also work on inventions under the hood, which does not mean that they are less important. When we developed the BME AI-Studio ecosystem it was a green field everywhere — from the technology to user interfaces, but also to the file formats that are the backbone of the entire ecosystem.
Together with Bosch Sensortec we developed multiple file formats that capture meta data, sensor data and relevant algorithm information in a comprehensive and meaningful way. This is a good example that green field innovations in software development have to be carried out carefully in order to progress fast later.
The new file formats enabled:
Compatibility between all hardware systems and software, allowing them to communicate and exchange data seamlessly
Efficiency in data storage and transmission, reducing file sizes and improving processing speed
Human-readable exchange of information between different software components of the ecosystem (e.g. desktop application, mobile app, sensor board)
Error reduction and automatic testing functionalities through schema checking
Flexibility though customizability and expandability for future developments
Automated schema check validations for file formats ensure consistency and interoperability between various components of the BME AI-Studio Ecosystem.
At Intervall, we are used to developing completely new things. That's why we often get involved in projects at a very early stage, whether it's a small trade fair stand or an entire EV charging ecosystem. Together with our customers, we love to create something new and unique.
Software Engineering
At Intervall, we develop digital products for challenging problems which often require complex solutions. So it is only logical that we also take care of the task of software development. That involves the concept and design, but also the programming and testing of various software applications. With our team of internal and external developers we have created many successful software projects on multiple platforms and with a variety of different technologies. Modern Toolchains must be fast, flexible, reliable and secure — but each project needs its unique tech stack.
Linux / Windows / MacOS / iOS / Android / Web / Python / Rust / JavaScript / Electron / React / Svelte / Wolfram Language / TensorFlow / PyTorch
Users of BME AI-Studio are supported along their way with a comprehensive ecosystem consisting of a desktop application, mobile apps and hardware as well as a server version for automated applications.
Computation-driven software development.
When it comes to ensuring quality in software development, automated processes are key to success. The moment you automate something you have to design the process carefully in order to make sure that it will work under all circumstances.
This approach shifts our focus to edge cases, addressing potential challenges proactively. It also makes use of the computational power, so automated tests can be run on every iteration of the software with almost no effort. Design and Computational Thinking come together for ensuring software quality.
With BME AI-Studio we have fully automated the CI/CD pipeline on Github:
A version-controlled code base with fully automated build processes for all major platforms
Automated unit test, integration test, as well as automated checking for security vulnerabilities
This is crucial when designing and implementing a whole software ecosystem.
This is also true for complex data analytics and especially for machine learning pipelines. It is less important to be 100% bug free or security compliant, when exploring new data science approaches, but a systematic approach and reproducibility is key for automated experiments. Unit tests can be used to assert correctness, although the algorithms are in a constant flow of change.
Together with Bosch, we have not only developed AI for gas sensors, but also laid the ground work for their Bosch Motion Sensor AI pipeline, separating the core machine learning source code from internal and external application code.
“Intervall is a reliable partner for us at Bosch Sensortec and we can highly recommend them for fast and scalable custom use case development.”
Dr. Richard Fix, Portfolio Manager Bosch Sensortec
Simulations with an event-driven architecture.
We always like to think about the possibilities of data analytics when developing software systems. We did so when we developed the frontend and backend components for MAHLE chargeBIG.
The architecture is designed in a strict event-driven way, in which we are not storing state but the events that change the system state.
This has profound implications for later data analytics, because it allows you to simulate alternative system behaviors. For instance: more complex pricing models, reservation features or complex load management.
Compared to the usual approach of parameterizing the system, event-driven architectures and the datasets that evolve from such systems allow you to change system parameters you haven’t thought of in the beginning. One example is the influence of intelligent load management that affects nearly all user touch points. Because we store all user interactions (and also hardware events) in an Event Store we can basically simulate every solution in the space of possible backend logics.
Consistent entries in an event store allow for capturing, restoring or simulating any state of a complex system.
Finding the right technical solution for a product concept is an exciting and responsible task that we at Intervall enjoy tackling together with our customers. In software development, it is important to be innovative and thoughtful at the same time - both playful and serious - we like to work with wit and rigor at the same time.
Techno Pioneers
Together with our customers we have a vision of what it means to be truly innovative. To create something new and substantial, to go where no one has gone before, to be courageous and try out new things also involves the possibility of failure. We are thankful that in the past our customers had the trust and faith in us to be bold, to dare something and in the end to be the first one, to pioneer new ways, to truly invent something.
The combination of speed and innovation sometimes leads to unprecedented achievements.
Neural net based algorithms can interpret the temperature-cyclic resistance data of the BME688 gas sensor in such a way, that individual electronic fingerprints of specific compositions of the gas atmosphere can be reliably recognized.
The world's first gas sensor with artificial intelligence.
The vision of pioneering innovation is clearly exemplified in our journey with Bosch. In this collaboration, we embraced the challenge of developing the world's first gas sensor with AI. It was due to the excellent hardware development of the Bosch Sensortec BME688 that we were able to work on a truly innovative gas sensor.
We developed the data analytics that takes full advantage of the temperature cyclic behavior to create the first gas sensor with AI on the market that can be programmed freely to detect (almost) whatever you want.
With around 18 months prior to official market release we had to work fast to explore various machine learning technologies in order to choose the right one for the specific requirements.
Breaking new ground with German Eichrechtsamt.
Similarly, together with MAHLE chargeBIG, we ventured into uncharted territory by challenging the existing EV charging solutions. We wanted to be the first ones who are allowed to bill for EV charging in Germany in accordance with calibration law.
In close collaboration with the Eichrechtsamt and VDE Prüf- und Zertifizierungsinstitut GmbH we developed a digital solution that uses cryptographic technologies to provide a safe and secure transmission of meter readings to the customer.
This part of the software was encapsulated and equipped with appropriate interfaces in such a way that it can be operated for many years without changes after evaluation by the calibration authorities. This means that new and expensive reevaluations can be avoided during the continuous further development of the overall software. Together with MAHLE we developed the first fully digital EV charging solution compliant with calibration law, pioneering a path for all other charging infrastructure providers.
Cryptographic signatures of meter readings allows reliable tampering checks on the customer's chargeBIG mobile app and thus fulfill the standard of the German Eichrechtsamt.
Algorithmic music for a swiss banking software
Our pioneering spirit is not confined to technical innovations alone. In an artistic endeavor with Finnova we once again broke new ground by being the first to develop a modular synthesizer that has a specific programming reflecting the interdependencies of the Finnova Product Portfolio as a switching matrix.
The result is a combined artwork of an electronic musical instrument, multiple musical pieces (each for one software solution) and a photographic documentation that was used for marketing purposes.
The cabling of the modular synthesizer is a symbol of Finnova's interconnected software ecosystem.
Detail of a transition matrix between different software modules
Graphical representation of the transition matrix
In every venture, whether it's developing groundbreaking AI-supported gas sensors with Bosch, redefining EV charging standards with MAHLE chargeBIG, or merging technology with art in our collaboration with Finnova, we consistently push the boundaries of what's possible. These examples underline our ongoing commitment to not only participate in the technological landscape, but to lead and redefine it.
Interdisciplinary at Heart
We are a team of interdisciplinary experts including designers, physicists, data scientists, software developers, photographers and artists. Our focus is on the actual work, and we maintain flexibility in the type of employment relationship.
In addition to our core team, we have a network of specialized freelancers who support us with their expertise in individual projects.
To understand the world includes to understand its limits. Planet Earth has been a good home for mankind ever since. We are living in the most interesting times since we as humans realized the finite nature of our planet's resources and the limits of the protective atmosphere surrounding us.
At Intervall, we try to contribute to the emerging global sustainability effort by first doing the obvious. Intervall is a paperless office with energy-saving devices and LED lighting. Additionally, our choices of technologies reflects our commitment to energy-conscious computing.
We are proud to have the privilege of collaborating with our customers on projects towards a more sustainable future.
We joined bosch in the process of acquiring a CDP rating.
We are proud to contribute to the Metal Recycling of Aurubis and their efforts to circular economy – working for a more resource-efficient world.
Through our innovative work on the BME688 gas sensor we empower Dryad in their mission to reduce global CO2 by 20%.
Reducing the computational effort of neural nets not only makes them run faster on limited hardware, but also reduces the energy consumption dramatically.
In our work for chargeBIG we drive expansion of charging infrastructure and thus the electrification and reduction of pollutants in the mobility sector
Rust is a modern but also highly efficient and thus green technology, saving up to 30times the energy consumption when compared to Python.
Through our strategic project selection and commitment to energy efficient technologies, Intervall is not only committed to sustainable practices in our operations, but also proudly contributes to the global mission of creating a more sustainable and resource efficient future.
Academia
The scientific approach is deeply intertwined with our concept of Design and Computational Thinking. Our approach to observing the world and collecting empirical information is manifested in our practices of user research and data collection. Systematic analysis of the findings and the formulation of hypotheses are at the heart of our work. We like to experiment, to verify or falsify different theses – building on existing scientific knowledge means standing on the shoulders of giants.
We feel honored to collaborate with our partners in academia.
Man is a Machine. Man is not a Machine.
The world can be understood in a mechanistic manner, as a sequence of cause-effect chains, as a result of constant execution of a routine. In this image, the human body is a chemical-biological machine, and the mind is an information processing engine emerged from it. In accordance with that, modern psychology argues that neuronal computations make up human perception and thus the state of consciousness. Consequently, cognition and consciousness can be interpreted as a kind of »computation« (computational theory of mind [1]).
In general, computation can be discussed detached from the respective physical implementation. One speaks of Turing-complete machines which are computationally universal [2]. CPUs are the common example. However, the implementation of human consciousness is linked to exactly one »biological computer«, namely the associated human brain and its neurons (biological computing [3]). Humans and their minds are certainly far from understanding this »biological computer«, if that's even possible at all. Emerson M. Pugh put it in a quote this way: “If the human brain were so simple that we could understand it, we would be so simple that we couldn’t.” This fact is also reflected in the structure of our sciences. Psychology, sociology and ethnology can not be reduced to biology, chemistry and physics in a reductionist sense. The natural sciences are separated from the social sciences by multiple boundaries of emergence [4].
The resulting gap between the scientific disciplines invites us to consider diverse questions from their respective peripheries. Coming from one side, we can take the human perspective, conduct behavioral research, analyze needs, or do ethnological studies. Coming from the other side, we can explore fundamental scientific contexts, set up experiments and conduct series of measurements. These are two different perspectives on the world.
Here we see parallels to our idea of design and computational thinking described above, which also represents two perspectives for approaching various challenges. Design advocates the human side and puts the user at the center, while computational thinking is thinking like a machine and puts data at its heart. Two complementary approaches merge: intuition, creativity, emotionality, empathy and art on the one hand – stringency, analytics, rationality, precision, science on the other.
This comparison has limits and by no means intends to deny the stringency of the social sciences, just as it does not want to neglect the importance of intuition in the natural sciences. Rather, it is meant as a metaphor and inspiration for the reader, and may be understood – especially in case of disagreement – as an invitation to engage in conversation.
Intervall was founded in 2019, 1000 days ago. Every year, we like to look back in time and take inspiration from the history of Design and Computation in a broader sense, which we then turn into a poster.
A Crack in Everything, that's how the Light gets in.
Through openness, one can learn new things,
though imperfections, one can achieve beauty,
through flaws, one can gain new understanding,
through reflection, one can gain insight from the past.
Through openness, one can learn new things,
though imperfections, one can achieve beauty,
through flaws, one can gain new understanding,
through reflection, one can gain insight from the past.
Taking and giving inspiration is the engine of human culture and drives us in our work every day. We draw inspiration from many sources, some of which may also inspire you ...
Join the Team
Striving for excellence within an ongoing learning process is at the heart of Intervall. We question the status quo to re-think how things might be in the future. Interdisciplinary exchange is the basis for an individual, personal development and the constant reconsideration of our own approaches.
We are looking for excellent people from different domains. Software developers, data scientists, architects, craftsmen, storytellers and designers reinvent themselves at Intervall.
