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Automotive

Apply data analytics and AI to personalise the customer experience in pre-sales and aftermarket, better forecast demand, optimise operations and improve services.

Data Science and related technologies are revolutionizing the automotive industry. By leveraging the power of predictive analytics, machine learning, and artificial intelligence, automakers can unlock a wealth of insights that can help them to reduce costs, increase customer satisfaction and improve safety. Examples of value created by these technologies include:


  • Optimizing vehicle assembly and production processes

  • Improving customer experience and satisfaction

  • Enhancing driver safety and convenience features

  • Developing predictive maintenance solutions



For inspiration, feel free to browse through some of the highlighted  case studies below.

Michael Gramlich

Automotive

Related Case Studies

Increased data and process transparency to show leftover resource potential

Optimising Resource Efficiency

Increased data and process transparency to show leftover resource potential

Minimising the amount of scrapped material by identifying early which products cannot be fully finished

Smartly Detect Product Defects in Production

Minimising the amount of scrapped material by identifying early which products cannot be fully finished

Identyfing location factors before expanding to new places

Charging Station Allocation

Identyfing location factors before expanding to new places

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