AI-POWERED MEDITATION PLANS
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COMPANY
Mindify
ROLE
UX Designer
EXPERTISE
UX/UI Design
YEAR
2024
Generated using Gemini Pro, using real high fidelity prototype images
Project description
ZenMind is an AI-powered meditation app designed to provide personalized meditation sessions based on user behavior, mood, and stress levels. The goal of this project was to create a seamless and calming user experience that adapts to users' emotional and mental needs in real time.
The Why
Phone Dependency & Costs: Static A4 schedules lack real-time updates, forcing users to buy expensive mobile data plans just to use transit apps.
Unpredictable Waits: Passengers wait outside in bad weather because they fear missing their bus if they wait inside the terminal.
Inaccessible Info: Hard-to-read wall maps and language barriers leave users confused, forcing transit staff to constantly answer wayfinding questions.
Timeline
From explorations to final designs in 5 weeks while working with multiple projects at the same time
Background The initial version of the app lacked personalization, and users found it difficult to discover meditations that suited their preferences. There was also a need for a more engaging user interface that aligned with the app’s core mission—reducing stress and promoting mindfulness through tailored experiences.
The Who
The Problem Statement
Commuters face confusion & delays. No real-time info makes navigation hard, especially for seniors & newcomers.
Process
This category details the step-by-step approach taken during the project, including research, planning, design, development, testing, and optimization phases.
Phase 1: Discovery & Scoping
Conduct initial desk research to understand the domain.
Brainstorm core problems and identify key stakeholders.
Connect with stakeholders and define clear research goals.
Research & Planning
Conducted market research to identify existing scheduling challenges and user preferences. Defined target audience segments and outlined key features based on user needs and market trends.
Design & Prototyping
Collaborated with designers to create intuitive user interfaces and interactive prototypes. Iteratively refined designs based on user feedback to enhance usability and visual appeal.
Development & Implementation
Leveraged agile development methodologies to build the scheduling app from the ground up. Prioritized feature development based on user feedback and technical feasibility. Implemented AI algorithms to analyze user behavior and optimize scheduling recommendations.
Phase 2: Generative Research
Gather field notes and conduct field surveys to observe real-world context.
Synthesize early findings to narrow down and define the specific problem statement.
Observational data revealed a distinct behavioral split. While youth checked phones, seniors and newcomers entirely bypassed the static, clustered wall maps in favor of asking ticket booth staff.
Image created using Gemini Pro, using real insights recieved from field observations
Phase 3: Primary Research & Analysis
Recruit target participants for in-depth studies.
Conduct user interviews, contextual inquiries, and detailed surveys.
Analyze the qualitative and quantitative data to uncover actionable insights.
We also tested a low fidelity version of our prototype
Research Insights- Low & Mid Fidelity
Phase 4: Design & Validation
Build interactive prototypes based on research findings.
Conduct usability testing to validate and refine the design.
Synthesize final results for the final pitch presentation.
Phase 3 & 4 were conducted simultaneously where we would build low medium or high fidelity protoypes, test them out and go back to the drawing board.
Iterations
Based on user and stakeholder feedback collected during the previous phase, we optimized and iterated the overall solution during the medium-fidelity prototype stage.
Solution
The resulting AI-powered scheduling app offers a seamless user experience, allowing individuals and businesses to effortlessly manage their schedules.
Multimodal Alerts (Audio & Visual): The physical kiosk is lined with an LED light strip that flashes red when a bus is arriving, while a built-in speaker simultaneously announces the arrival out loud. On the screen, the specific bus route map visually moves ahead to match the alert.
Cognitive & Visual Accessibility: The digital interface utilizes large fonts, high-contrast text, and a simplified layout to reduce cognitive overload, specifically targeting seniors and users who are not tech-savvy.
Voice-Activated & Multilingual: To assist newcomers and users with limited mobility, the kiosk supports multiple languages (including English, French, and Simplified Chinese) and features audio input so users can speak to the kiosk instead of typing.
Physical Handout Dispenser: Recognizing that not all users want a purely digital experience, the kiosk includes a dispenser that provides physical handouts detailing which bus they need to take to reach their destination.
Real-Time System Integration: Replaces static, unreliable printed schedules with real-time transit data, displaying live delays and route changes to reduce user anxiety during bad weather or at night.
Results
Here, the outcomes and achievements of the project are highlighted, including user feedback, adoption rates, and industry recognition.
User Retention
The personalized meditation recommendations led to a 30% increase in user retention within the first 3 months of launch.
User Satisfaction
Post-redesign surveys showed a 40% improvement in overall satisfaction due to the app’s more tailored experience.
Engagement
Daily meditation completion rates increased by 20%, as users found the sessions more relevant and engaging.
We won Bronze among 40 entries at the HCI Conference of Montreal for this project in 2026
