Predictive Maintenance
Prevent defects in production machines and vehicles with predictive maintenance methods.
AI in Automotive
AI in the Automotive Industry
We assist companies in the automotive industry in effectively leveraging Data and AI to enhance products and services, optimize processes, and identify new business models.
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Your Experts for Artificial Intelligence in Automotive
How AI Creates Value in the Automotive Industry
The automotive industry is on the brink of a new era, marked by emerging technologies. Artificial Intelligence (AI) in the automotive industry is one of the driving forces revolutionizing the sector, impacting all areas and processes: from production to vehicle development and driving operations – the integration of AI offers numerous advantages for manufacturers and customers alike. AI in the automotive industry leads to significant efficiency gains, cost savings, and innovations.
A standout example of the transformative power of AI in automotive is the development of autonomous vehicles. Thanks to advanced AI technologies for environmental perception, object recognition, and decision-making, self-driving cars can analyze their surroundings in real-time, make decisions, and navigate traffic safely. Thus, AI in the automotive industry not only marks a milestone in vehicle development but also paves the way for safer and more efficient mobility solutions.
AI-powered systems also enhance maintenance efficiency. Predictive maintenance is an application area where AI offers significant benefits to the automotive industry. AI algorithms continuously analyze vehicle data to detect and address potential issues early before they lead to severe defects. This not only increases vehicle reliability but also saves companies costs and resources.
Consult with our experts on customized AI solutions in the automotive industry, such as EBIT Forecasting, predictive maintenance, data integration, supply chain pricing strategies, or personalized recommendation systems, to harness the full potential of AI in your business.
Use cases for data science and AI in automotive
KPI and Sales Forecasts
Make decisions based on reliable forecasts of your KPIs such as sales, turnover, costs, liquidity or EBIT.
Residual Value Forecast
Determine the residual values of leased vehicles efficiently and precisely with the help of data-based solutions.
Digital Assistants
Make your driving experience more personalized with IoT applications, voice control, and digital assistants.
Analyse Telematik-Daten
Base your product development and marketing decisions on the analysis of usage and vehicle data.
Personalized Product Configuration
With AI, you can ensure that your customers receive exactly the product configuration that suits them.
Quality Control
Control and optimize the quality of your products using data and artificial intelligence.
Supply Chain Management
Optimize your order, inventory and production management based on demand and supply forecasts.
Applications of AI in Automotive
The use of Artificial Intelligence (AI) in the automotive industry (AI in automotive) is driving profound changes. By integrating AI in automotive, companies can increase the efficiency of numerous processes, improve the quality of their products, and enhance the customer experience. With a suitable AI strategy, AI training measures, external AI consulting, and tailored data science consulting, unprecedented opportunities arise.
AI in automotive plays a crucial role not only in predictive maintenance and quality management to reduce warranty costs and avoid costly recalls. AI in automotive also improves existing driver assistance systems and enables the development of new functions. Beyond intuitive applications of AI, numerous use cases for AI in automotive emerge: Visual inspections and quality controls, for example, can be optimized through AI-based image processing, enhancing production quality. These developments further increase safety and comfort and build trust, proving that artificial intelligence brings significant benefits to the automotive industry.
Another technology making AI in automotive an exciting future field is Natural Language Processing (NLP). NLP enhances the interaction between driver and vehicle, leading to a more intuitive operation of infotainment systems. Additionally, AI can even assist automotive companies in optimizing design processes and accelerating the development of new vehicle models, resulting in more innovative and efficient products.
Eine durchdachte KI-Strategie ermöglicht es Unternehmen, ihre spezifischen Ziele klar zu definieren, Anwendungsbereiche zu identifizieren und den Einsatz von KI-Technologien gezielt zu steuern. So wird sichergestellt, dass sämtliche KI-Initiativen auf die übergeordneten Unternehmensziele abgestimmt sind und eine solide Infrastruktur, verlässliche Datenbasis sowie das notwendige Fachwissen vorhanden sind. Eine strategische Planung minimiert Risiken, steigert die Akzeptanz und legt den Grundstein für nachhaltigen Erfolg mit KI.
Unsere Beratung zur KI-Strategie bildet das Fundament für die datengetriebene und KI-basierte Transformation Ihres Unternehmens. Gemeinsam erarbeiten wir, wie Sie die Transformation strategisch umsetzen und die erfolgversprechendsten Einsatzmöglichkeiten für Ihr Unternehmen auswählen können.
Procurement-Suite
In this project, we developed a comprehensive procurement suite to support buyers, guiding the purchasing process from finding relevant suppliers to price negotiation.
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Application for creating Risk Reports
To address the issues of missing stability and lack of interactivity in risk reporting, an R Shiny application integrated into a CI/CD pipeline was developed. The goal was to meet industry-specific security standards while simultaneously improving the user experience.
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Operating Model
In this project, we worked closely with our client to develop an operating model for a newly established analytics department. This operating model defines collaboration processes to efficiently implement the strategic vision.
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Automated Deployment of R Shiny Applications
To implement a controlled and automated process for the deployment of Shiny applications, we designed and implemented a CI/CD pipeline solution for our client.
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Prediction of Quality Issues
In this project, we developed a machine learning algorithm that identifies emerging quality issues in the field and prioritizes them by importance.
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Sales Forecasting Automotive
In this project, we developed a machine learning model for car sales forecasting at both the overall and type-class levels for an international automotive corporation and implemented it into the client's IT infrastructure.
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Customer Segmentation Automotive
In this project, we developed a statistical model for customer segmentation based on panel survey data from our client, which specifically groups and analyzes customers with similar needs.
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Big Data Analysis Tool Automotive
For this project, we developed a scalable analysis tool for load collective and vehicle data in the terabyte range for our client.
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Big Data Analysis Dashboard
For this project, we developed a scalable online dashboard for our client in the field of big data analysis and telemetry, covering the usage of vehicles worldwide.
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Department-wide Data & Analytics Training Concept
For our customer, we developed and implemented a department-wide Data & Analytics training concept. It consists of four separate training paths to achieve specific qualifications.
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Adoption of Kubernetes Operating Platform
In this project, we helped our customer implement Kubernetes as an operating platform for cloud applications across the company, starting with a proof of concept (PoC) and ending with the completion of a minimum viable product (MVP).
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Forecast of Residual Value for Leased Vehicles
Together with our customer, an international automotive group, we developed a tool for predicting residual values of leased vehicles in this project.
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Discount Optimization
The project focused on the data-driven optimization of distributing discount budgets across individual vehicles for targeted inventory management.
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Time Series Forecasting Engine
In this project, we collaborated with our client to develop and implement a forecasting engine for arbitrary time series data.
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Demand Forecasting
To increase the accuracy of our client's demand planning, we developed a demand forecasting engine that combines a wide variety of machine learning and deep learning algorithms to predict the demand for over 20,000 products within the next 24 months.
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Prediction of Investment Costs
In this project, we developed a machine learning model for our client to predict annual costs and the timing of expected payments for investment projects.
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Supplier Recommendation Tool
In this project, we predicted the expected failure times of components and engine parts by applying machine learning and statistical models.
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Predictive Maintenance in Automotive
In this project, we predicted the expected failure times of components and engine parts by applying machine learning and statistical models.
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EBIT Forecasting
In this project, we developed and implemented a machine learning model to forecast the expected EBIT (Earnings Before Interest and Taxes) for the next one to three months.
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Introduction of a standardized framework for data integration at an automotive manufacturer
We developed a standardized framework for an automotive manufacturer to integrate data sources into a data lakehouse more efficiently and reliably.
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Optimizing the supply chain pricing strategy for an automotive supplier
We optimized the supply chain pricing strategy for an automotive supplier to achieve greater transparency in cost structures, optimized margins and greater efficiency throughout the supply chain.
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Increasing in-car service sales through a personalized recommendation system
We developed a personalized recommendation system for a car manufacturer that increases in-car service sales and improves customer satisfaction.
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A standardised reporting platform for the automotive industry
By leveraging cutting-edge web technologies, we developed a customized platform that simplifies access, usage, and management of data science reports while also being expandable.
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Efficient Fleet Planning through Frontend Data Visualization
We developed a custom frontend that equips our client for future challenges in strategic portfolio planning.
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Production Data Analysis with a Personalized AI Assistant
Our client sought a solution to access production data in real-time and natural language. We developed a generative AI assistant that makes complex data user-friendly and accessible without deep technical knowledge.
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Our strength
Our ecosystem enables a holistic view of data & AI.
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Tools, Partner & Technology
10+
years of experience in Data Science, ML, and AI
100+
clients from 10 industries and growing
85+
experts from more than 17 fields of study
1,000+
successfully implemented Data and AI projects
Data Science in Automotive
Alongside Artificial Intelligence, Data Science also plays an increasingly important role in automotive. By analyzing large data sets, valuable insights can be gained to optimize production processes and develop innovative solutions.
One example is the optimization of supply chains with Data Science in automotive. By evaluating data from various sources, bottlenecks and inefficiencies can be identified and resolved. This leads to more efficient production and better utilization of production capacities. Another application area for Data Science in automotive is personalizing the driving experience. By analyzing user data, car manufacturers can offer tailored features and services that precisely match customers' needs and preferences.
The future of the automotive industry is digital. AI and Data Science are the keys to this transformation. Data Science and Artificial Intelligence in automotive enable innovative services and new data-driven business models for connected vehicles, unlocking additional revenue streams. Personalized, data-driven services and offerings, supported by AI and data, can strengthen customer loyalty and enhance the driving experience.
Our services
AI Consulting
Our consulting services focus on both technical and methodological skills, data literacy, and data culture, utilizing interactive and inspiring learning methods. We provide training for beginners, specialists, and executives.
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AI Starter Offerings
Are you just beginning your data and AI journey? We offer various workshops, training sessions, and ready-to-use AI solutions that are perfect for taking the first steps with data science and AI.
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AI Solutions
We develop data science and AI solutions tailored to your requirements. We support you from the initial idea to the productive solution and ensure smooth operation thereafter.
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AI Trainings
Whether technical or methodological skills, data literacy, or data culture - our formats rely on interactive and inspiring learning methods. We train beginners, specialists, and executives.
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Contact your experts for data and AI in Automotive
01
Free consultation
Discuss your challenges and goals in the area of Data & AI with us.
02
Tailored offer
Receive a customized and transparent offer.
03
Presentation & contract award
We present our approach to all relevant stakeholders.
04
Onboarding with project team
Our dedicated project team takes care of your needs.
Frequently asked questions and answers
How is Artificial Intelligence (AI) transforming the automotive industry?
AI is revolutionizing the automotive industry by making processes more efficient and enabling new technologies such as autonomous driving. It plays a key role in the development of self-driving vehicles, which can analyze their surroundings in real-time and navigate traffic safely thanks to AI. Beyond vehicle development, AI also improves production and maintenance, leading to significant cost savings and higher product quality.
What is Predictive Maintenance and how does the automotive industry benefit from it?
Predictive Maintenance is an AI-driven method to predict maintenance needs. In the automotive industry, algorithms continuously analyze vehicle data to detect potential issues early before they lead to costly failures. This technique increases vehicle reliability, reduces downtime, and saves both manufacturers and customers time and costs.
What other applications does AI have in the automotive industry?
In addition to autonomous driving and predictive maintenance, AI is used in many other areas. These include driver assistance systems, which are enhanced by AI, as well as visual inspections in production to optimize quality assurance. Moreover, Natural Language Processing (NLP) improves the interaction between driver and vehicle. AI can also help optimize supply chains and enable personalized driving experiences.
