Acentrik is a blockchain-based data exchange platform developed by Daimler Southeast Asia, a subsidiary of Mercedes-Benz.
- Role Product, UI/UX Design Intern
- Timeline 3 Months
- Tools Figma, Miro, FigJam
Project Background
Acentrik is a blockchain-based data exchange platform developed by Daimler Southeast Asia (Mercedes-Benz Group). It connects multiple user types, including Data Providers, Data Consumers, and Administrators, enabling secure and efficient data sharing within organizations.
Main Responsibilities
During my time at Acentrik, I assisted with designing platform features such as integrating custom Docker images, allowing users to tailor their data processing environments to specific requirements.
A centralized platform for browsing, filtering, and purchasing blockchain-based datasets and algorithms.
Displays in-depth information, pricing, and technical details of a selected dataset or algorithm for purchase or computation.
Research & Ideation
Our Team conducted whiteboarding and affinity mapping sessions to explore various “How Might We” opportunities collaboratively with developers and product owners. These insights helped shape user personas that captured key motivations and pain points, as well as user stories that outlined real usage flows and goals.
Defined key personas representing different user groups to understand their goals, frustrations, and motivations when interacting with the Acentrik platform.
Developed user stories for CDI and Algorithm Acknowledgement features, mapping “Happy” and “Unhappy” flows to capture both ideal user experiences and potential pain points.
Lofi Prototyping & Testing
We created low-fidelity wireframes to visualize key interactions for the CDI and Algorithm Acknowledgement features. These prototypes were reviewed internally and refined based on feedback. Later, usability testing sessions were conducted to gather user insights through targeted questions, helping validate design decisions and uncover usability gaps.
We invited three users to walk through key task flows and share their thoughts along the way. Their feedback helped us spot friction points and refine the overall user experience.
Final compute dataset flow validated by our users
