What is an Automotive Digital Twin?

A digital, cloud-based clone of a physical vehicle designed to detect, prevent, predict, and optimize through AI and real-time analytics.

Connected vehicle data is vastly underutilized across the automotive industry and its customers. CarTwin is unlocking its value by creating an integrated data ecosystem to drive actionable insight and predictive analytics to address the industry’s most pressing challenges.

Our digital twin technology enables a diverse set of automotive use cases that power new innovations by connecting physical and digital worlds providing real-time operational awareness of vehicle, component, and manufacturing performance.

There is no other option that is more nimble, more cost-effective, more cutting-edge and more grounded in the real-time reality of how your business actually operates.

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With a digital twin, an organization can monitor performance, predict the impact of changes, identify areas for improved productivity or customer service, and evaluate new operating models. This pairing of the virtual and physical worlds allows analysis of data and monitoring of systems to head off problems before they even occur, prevent downtime, develop new opportunities and even plan for the future by using simulations.

Learn more about our digital twin technology.

WHO ARE OUR CUSTOMERS?

At CarTwin, we’re focused on how AI can help our customers across three core asset phases: Manufacturing, Management, and Maintenance.

Commercial Fleets

Empowering fleets with predictive analytics to drive efficiencies, reduce downtime, and improve customer satisfaction

Automotive Manufacturers

Simulating production, quality, and operational performance to enable innovations in R&D and product development

OEM & Aftermarket

Proactively improve design with different raw materials and predict replacement demand based on driving behavior

Solutions That Solve for Real World Problems.

Whether increasing fleet performance and optimizing supply chains, enabling open innovation to bring new models to market faster and safer, or producing more durable parts to extend the life of a vehicle, CarTwin’s cloud-based solutions help companies accelerate the commercial adoption of artificial intelligence to drive operational efficiencies and revenue growth.

Our easy-to-use technology bolts on to your existing systems and   products to create a seemless user experience, holistic view of key performance indicators, and predictive insights to help you make better decisions, faster.

Predictive Fleet Maintenance

Identify preventative repairs before breakdowns occur to reduce total expected cost of maintenance, decrease vehicle downtime, and mitigate risk to your commercial fleet.

Fleet Telematics AI

By classifying events correctly based on preset parameters, fleet managers can continually refine classifications to accurately assess fleet operations on an ongoing basis.

Predictive Component Failure

Virtually experiment to proactively improve design with different compounds and raw materials and predict aftermarket part replacement demand based on driving behavior.

Automotive Design Simulation

Fully flexible, end-to-end solution to validate each step of vehicle design in order to identify problems and possible failures before producing real vehicles or ramping supply chain.

LATEST NEWS

Revolutionizing Automotive Markets with Digital Twin Technology

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Unlocking Advanced Possibilities of AI Among Commercial Fleets

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Corey Thompson

CEO, CarTwin

“The automotive industry has witnessed incredible transformation over the last decade. CarTwin represents the next chapter in its digital disruption. We’re leveraging artificial intelligence, industry expertise, and easy-to-use tools to provide the most complete Digital Twin technology blueprint available today.

More importantly, our solutions require little to no infrastructure improvements for our customers to experience significant competitive advantages. CarTwin reduces operational risk by predicting automotive and driver behavior and performance, while also carrying out efficient planning, forecasting, and automated decision making.”

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