Demand Forecast
Forecast the future transport needs of your customers reliably and at an early stage with data and AI technologies.
AI in Logistics
AI in the
Logistics Industry
We help companies in the logistics industry to effectively use Data and AI to optimize processes, improve supply chains, and identify new business models.
Trusted by Industry LEaders
Your Experts for Artificial Intelligence in Logistics
Applying Artificial Intelligence (AI) in Logistics
The logistics industry is undergoing a major transformation driven by the use of Artificial Intelligence (AI). AI in logistics offers a multitude of advantages, ranging from increased efficiency and cost reduction to the creation of new business models. Integrating AI into logistics is key to optimizing supply chains and enhancing competitiveness.
A prime example of the transformative power of AI in the logistics industry is the optimization of supply chains. Thanks to advanced AI technologies, companies can monitor their supply chains in real-time, make predictions, and respond more quickly to changes. This leads to better planning and a reduction in bottlenecks and delays – a crucial advantage in today’s fast-paced business world.
AI logistics systems also enable more efficient inventory management. Through continuous analysis of sales data and demand forecasts, AI can help logistics companies manage their inventory optimally and avoid overstock or shortages. This not only increases efficiency but also saves costs and resources.
Another crucial application of AI in logistics is chatbots. They offer a variety of useful functions in the logistics industry. AI chatbots are available around the clock and enable smooth customer interaction across various platforms such as websites and messaging services. These AI logistics chatbots can provide real-time delivery status and tracking information, increasing transparency and building customer trust. They also facilitate the management of order changes, cancellations, and product inquiries, promoting customer satisfaction and loyalty.
Consult with our experts for individual solutions in the field of Artificial Intelligence (AI) in logistics, such as predictive analytics, route optimization, data integration, or a personalized recommendation system, to fully leverage the potential of AI in logistics within your company.
Valuable use cases of Data Science and AI in logistics
Arrival Prediction
Predict and track the expected arrival time of transportation vehicles with data science and AI.
Predictive Maintenance
Recognize maintenance requirements and defects in your fleet vehicles at an early stage by using data science and AI.
Quality Control
Determine automatically and in real time the quality of transport goods from goods receipt to delivery.
Intelligent Warehouse Management
Use artificial intelligence to automate and improve manual processes in warehouse management.
Route Optimization
Optimize your transport routes and capacities based on data and AI based forecasts.
Utilization Forecast
Forecast the utilization of future transport capacities in order to be able to initiate measures at an early stage.
Fleet Monitoring
Gain visibility into your fleet by collecting and analyzing real-time telematics data.
How AI Optimizes Supply Chains
The use of AI in supply chains drives profound changes and opens up unprecedented possibilities. By integrating AI into supply chains, companies can increase the efficiency of numerous processes, improve the quality of their services, and optimize the customer experience. With a suitable AI strategy, AI training measures, external AI consulting, and tailored data science consulting, companies can elevate their supply chain to the next level.
AI in the supply chain plays a crucial role in predictive maintenance and quality management to minimize downtime and increase reliability. AI in the supply chain also enables route optimization and improves delivery accuracy. Through AI-based analyses, companies can design their transport routes more efficiently, thereby reducing costs and environmental impact.
AI algorithms analyze historical and current traffic data to calculate the best routes for delivery vehicles. This leads to shorter travel times, lower fuel costs, and a reduction in CO2 emissions. By using AI logistics systems, deliveries can be made more punctually and reliably, significantly increasing customer satisfaction.
An important application of AI in the supply chain is demand forecasting. AI algorithms analyze historical sales data, market trends, and external factors such as weather conditions to make accurate predictions about future demand. This enables proactive planning and reduces the risk of over- or understocking. By integrating AI into the supply chain, companies can better utilize their resources and improve their responsiveness to market changes.
Another exciting application of AI in the supply chain is the automation of processes. From order processing to inventory management to delivery planning – AI can help companies automate manual tasks, thereby increasing efficiency and minimizing errors. These developments significantly contribute to enhancing competitiveness and improving customer satisfaction.
LLM Workshop and Inhouse Data Analysis for Experts
Our client wanted to train their data experts in a hands-on workshop to gain a deeper understanding of modern LLMs and their potential applications on company-owned data.
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Dynamic Pricing in Aviation
In close collaboration with our client, we reviewed and optimized a newly developed model for calculating price elasticities in this project.
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Demand Forecasting Logistics
In this project, we developed a machine learning model factory for forecasting customer demand in the B2B sector and implemented it into the client's IT infrastructure.
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Predictive Steering in the Aviation Industry
To assess future risks in an airline's operations, we worked with the client to develop an application that uses machine learning to provide predictive guidance for operations.
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Analysis of freight traffic flows in R Shiny
In this project, we supported our client in the production and evaluation of forecast results for freight traffic flows. An R Shiny application was developed for interactive graphical and tabular analyses.
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R Shiny App for Logistics Disposition
In this project, we developed an interactive web app for the disposition of transport demands using R Shiny and JavaScript, and implemented it into our client's IT landscape.
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Scaling of Forecasting Models
In this project, we implemented an existing model factory for demand forecasting of over 10,000 entities in parallel into our client's IT infrastructure.
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Prediction of Flight Delays
In this project, we collaborated with our client to develop a machine learning model that predicts flight delays to support the ground operations team.
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Dynamic Pricing with Reinforcement Learning
In this project, we developed an autonomous pricing system that can automatically control the bid prices for continental flights.
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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
Whitepaper: AI in logistics
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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Elevate Logistics Processes with AI
The integration of Artificial Intelligence and Data Science in logistics allows for the optimization of numerous tasks and processes. These benefits begin with the analysis of large data sets, from which valuable insights can be gained to optimize processes and develop innovative solutions.
An example of this is the optimization of supply chains with AI logistics. By evaluating data from various sources, bottlenecks and inefficiencies can be identified and resolved. This leads to more efficient production and better utilization of resources. Another application area for AI logistics is the personalization of the customer experience. By analyzing user data, logistics companies can offer tailored services and products that are precisely aligned with the needs and preferences of customers.
When companies use AI in logistics, it is increasingly in the area of predictive maintenance. Through continuous monitoring of machine and vehicle data, AI algorithms can detect potential problems early and suggest maintenance measures before failures occur. AI in logistics increases the reliability and lifespan of machines and reduces maintenance costs.
The future of logistics is digital. AI and Data Science are the keys to this transformation. Data Science and Artificial Intelligence in logistics enable innovative services and new data-driven business models, opening up additional revenue streams. Personalized, data-driven services and offerings, supported by AI and data, can strengthen customer loyalty and enhance the overall experience.
Leverage the expertise of statworx to revolutionize your logistics with AI and data, and sustainably increase your competitiveness.
Contact your experts for Data and AI in logistics
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 does AI improve the efficiency of supply chains in the logistics industry?
AI enables real-time monitoring and prediction of supply chain processes, leading to improved planning and reduction of bottlenecks. Companies can respond more quickly to changes, thereby increasing competitiveness.
What role does AI play in route optimization in logistics?
AI analyzes data and forecasts to optimize transportation routes and capacities. This leads to more efficient transport paths, cost reductions, and decreased environmental impact.
How can AI monitor the quality of transported goods?
AI enables automated and real-time quality control of goods from receipt to delivery. This ensures consistent quality assurance and enhances customer satisfaction.
How does AI support demand forecasting in logistics?
By using AI, logistics companies can reliably and proactively predict their customers' future transportation needs. This allows for proactive planning and resource allocation to avoid bottlenecks.
