CloudMade
How CloudMed’s AI Builds the Bridge From Data to Delight
CloudMed aimed to revolutionize the automotive experience by developing AI/ML-powered solutions that create intuitive, seamless interactions between drivers and their vehicles, enhancing comfort and personalization through cutting-edge technology.
My Role
Lead Product Designer
At CloudMed, I played a pivotal role in bridging advanced AI/ML technology with user-centric design, ensuring our innovations were both practical and impactful. My contributions included:
- Data Collection and Research: Spearheaded design initiatives of gathering and analyzing data contextual data, forming the foundation for our ML models.
- UX Research and Prototyping: Conducted in-depth research and iterative prototyping to develop concepts that transformed complex AI insights into simple, intuitive user experiences.
- Technology Demonstration: Designed and showcased cutting-edge user experiences through technology demonstrators, including a fully operational Experience App, paired with Experience Car prototype and interactive CES exhibits.
- Client Integration: Collaborated with leading automakers to adapt and integrate CloudMed’s proposed UX solutions into their unique ecosystems, tailoring our technology to their brand identities and customer needs.
Initial Problem Statement
How can we make automotive AI truly intuitive and delightful for drivers while respecting their preferences and avoiding overreach?
Drivers don’t expect their vehicles to be smart, they expect them to simply work. But sometimes to simply work means to seamlessly adapt to their habits with zero input, as if anticipating their needs. Yet, most existing systems fail to deliver, relying on generic, rigid automation that lacks context and personalization. CloudMed’s mission was to bridge this gap by transforming raw data into adaptive, human-centric interactions that are intuitive, meaningful, and effortlessly aligned with drivers’ lifestyles.
Goals
Develop Adaptive AI/ML Experiences
Create a system that uses data to deliver highly contextual, personalized, and intuitive vehicle interactions, elevating the driving experience beyond traditional automation.
Showcase Innovation through Technology Demonstrators
Build prototypes and concept experiences, like the Experience Car and interactive stands, to demonstrate CloudMed’s capabilities at key industry events, including CES, and attract automaker partnerships.
Enable Seamless Integration for Automotive Brands
Design scalable, customizable UX solutions that integrate effortlessly with automakers’ existing systems, ensuring consistency across diverse vehicle models and maintaining each brand’s unique identity.
Approaching Discovery
To address these challenges, I conducted extensive discovery work, including:
Stakeholder Interviews
Engaged with engineering, product, and support teams to align on priorities and understand constraints, ensuring stability for legacy devices while planning for innovation.
Usability Testing and Prototyping
Conducted iterative tests during agile sprints, refining prototypes based on user feedback to validate ease of use and intuitive interactions.
Behavioral Data Analysis
Analyzed usage patterns to uncover key trends, such as the dominance of vertical video viewing, informing design priorities.
Performance Testing and Architecture Review
Evaluated UX impacts on streaming performance, identifying opportunities to enhance load times and maintain system reliability.
Key Insight
Drivers want their cars to adapt to their unique habits and everyday lives, not just follow generic rules.
Instead of relying on rigid automations, CloudMed’s AI uncovered subtle patterns in driver behavior—like using the passenger seat heater to keep food warm—and turned them into smart, intuitive features. By focusing on real-life context, the system delivered truly personal and delightful experiences that felt natural and effortless.
Implemented Solutions
Data Collection and Analysis Enablers
To power CloudMed’s adaptive AI, a robust data collection program was essential. This began with the creation of an intuitive data collection app, designed to simplify the process of monitoring and managing the hardware responsible for gathering driver behavior data.
Collaborating closely with the engineering team, I designed and guided the implementation of a user-friendly application that allowed seamless interaction with the data collection devices. The app provided real-time monitoring of device status, data quality, and collection progress, ensuring efficiency and accuracy throughout the process. It also offered clear feedback mechanisms, enabling quick troubleshooting when needed.
This system was crucial for CloudMed’s platform, as it was the basis for ML/AI training, bridging the gap between raw data and transformative user experiences.
Impact
Improved Workflow Efficiency: Engineers could monitor the performance of data-gathering devices in real time, reducing downtime and ensuring consistent, high-quality data.
Enhanced User Engagement: The app’s simplicity and intuitive design encouraged consistent usage, critical for building a reliable AI training dataset.
Scalable Data Platform: Enabled the rapid deployment of data collection devices across various environments, ensuring the platform’s scalability for future expansions.
Experience App
A key component of CloudMed’s innovation was a technology demonstrator app, which served as a versatile tool for researching, user testing, and refining use cases involving driver interactions between the car and phone.
The demonstrator app was custom-built to simulate a variety of real-world scenarios, enabling iterative testing of features like predictive AI suggestions, seamless phone-to-car transitions, and adaptive vehicle controls. By combining high-fidelity prototypes with live functionality, the app allowed us to validate assumptions, test user flows, and refine interactions with real drivers in realistic contexts.
To showcase our technology, we developed a working prototype based on the Golf VII, dubbed the Experience Car. This prototype, along with tech demo interactive stands and the Experience App, was presented at CES 2019 in Las Vegas, demonstrating the real-world application of our ML models.
Impact
Accelerated Development Cycles: Enabled quick iteration and feedback collection during research and testing phases.
Validated Use Cases: Provided actionable insights into how drivers interacted with the AI’s predictive and adaptive features, ensuring user-centric design.
Enhanced Collaboration: Served as a shared platform for cross-functional teams to align on use case development, from concept to implementation.
Seamless Integration with Automakers
CloudMed’s AI technology was designed to integrate effortlessly into various automotive ecosystems, enabling manufacturers to adopt and scale advanced predictive features while maintaining their unique brand identities.
To achieve seamless integration, adaptable UX frameworks were developed to ensure compatibility with a range of in-vehicle systems, including infotainment units, instrument clusters, and companion mobile apps. Collaboration with manufacturers involved:
- White-Label Solutions: Designed a customizable interface that allowed manufacturers to incorporate CloudMed’s AI while preserving their distinct design language and user experience.
- Scalable Frameworks: Developed a modular system architecture that ensured quick and efficient integration across diverse hardware and software platforms.
- Iterative Feedback Loops: Worked closely with manufacturers to refine features and ensure alignment with their specific market needs and user expectations.
This integration strategy bridged the gap between cutting-edge technology and practical implementation, setting a new standard for intuitive, AI-driven automotive experiences.
Impact
Contracts Brands: Multiple automotive manufacturers successfully integrated CloudMed’s technology into their vehicles, enhancing user experiences with minimal disruption to their systems.
Rapid Deployment: The scalable framework enabled swift rollout of AI features, reducing time-to-market for partner brands.
Unified User Experience: Maintained brand consistency while delivering cutting-edge functionality, ensuring a seamless experience for drivers across different vehicles.
Results
The implemented solutions led to the following outcomes:
1
Accelerated Innovation
The R&D platform streamlined development, enabling rapid prototyping, user testing, and refinement of adaptive AI features, driving faster innovation and impactful breakthroughs.
2
Wide Attention from Automotive Brands
CloudMed’s white-label solution attracted multiple automotive manufacturers, leading to successful integration in vehicles worldwide and driving widespread adoption of AI-driven personalization.
3
Scalable Technology
The flexible system architecture ensured smooth integration with diverse vehicle platforms, enabling rapid deployment of features and future-proofing solutions for upcoming innovations.
4
Acquisition by Stellantis
CloudMed’s groundbreaking work culminated in its acquisition by Stellantis, one of the world’s leading automotive groups, validating the company’s vision and success in transforming the driving experience.
Learnings
and Takeaways
The CloudMed experience offered invaluable lessons in developing adaptive automotive AI/ML.
Context is King
Understanding real-world use cases, like heating the passenger seat for takeout, highlighted the importance of designing context-aware solutions that truly resonate with users’ needs.
Collaborative R&D Accelerates Innovation
Cross-functional teamwork and rapid prototyping fostered creativity, enabling swift iteration and refinement of complex systems.
Scalability is Key
Building adaptable, modular systems ensured seamless integration with diverse automotive brands, paving the way for widespread adoption of cutting-edge AI solutions.
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