We use data to create predictive work models. Using artificial intelligence and machine learning, we can make day-to-day work easier and more efficient, not just for a specific group of users but throughout the value chain.
We consider both the feasibility from a data standpoint and the profitability of potential projects, allowing you to benefit from our products from the concept phase right through to daily operations. We combine your data and our expertise to develop the right solutions. Why not discover what we have to offer?
Advanced analytics involves using sophisticated techniques and tools, such as machine learning, predictive modeling, and data mining, to analyze complex data sets.
Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and human language.
Deep Learning is a subset of machine learning that uses neural networks with many layers (hence "deep") to model and understand complex patterns in data.
AI research encompasses the study of techniques and algorithms that enable machines to perform tasks that typically require human intelligence.
We may not actually be able to predict the future, but we can certainly make it less of a mystery.
The first step is to conduct a workshop to establish what your needs are and what data and data sources you have available.
We then work together to develop ideas and solutions and clarify the key elements of machine learning, big data and artificial intelligence. We will review your data and the data quality in order to determine data readiness.
Result of Phase 1:
We will work with you to draw up an initial use case and test it using your existing data. This will result in a first prototype that will deliver the first measurable results for your department – providing real data and genuine benefit.
Result of Phase 2:
The prototyping process involves developing a minimum viable product (MVP). With the introduction of more users, more data, additional markets and additional functionalities, this MVP develops into the fully formed, finished product. A process of continuous and comprehensive testing during the development phase results in optimum performance of the end product.
Result of Phase 3:
Our teams have a flexible, interdisciplinary structure, which means that we are able to deploy the most suitable people at any point along the automotive value chain. Another benefit of harnessing this wealth of different perspectives is that we are able to identify completely new correlations and links and apply that knowledge in joint projects.
Our teams, made up of experts from a wide range of disciplines spend their days turning one of today’s most important assets – data – into a tool to provide customized, user-oriented products and applications.
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