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App Screen with open sidebar
App Screen with open sidebar

AcuTick AI

Precision-powered AI for real-time tick identification and risk analysis.

Year

2025

Timeline

6 months

Scope

User research & analysis

UX and UI design

Usability testing

Role

As the sole UX designer, I led the overall design direction of the project, while collaborating with 3 developers and a product owner

Mission & Design Goal


When a tick bite happens, uncertainty can be scary. Most people don’t know which tick bit them, what diseases it might carry, or what steps to take next. That’s where AcuTick AI comes in — a human-centered app designed to turn complex science into reassurance.


My goal was to create an experience that helps users remain calm, after discovering a tick by providing instant, reliable and empathetic information. From identifying tick species to tracking bites and symptoms, AcuTick AI empowers users with knowledge, control, and peace of mind.

Problem


Exploration & Discovery

In this early discovery phase, I also explored the broader ecosystem through:


Other Discovery activities conducted:

  • Market Research: Analyzed public health data and emerging trends in digital diagnostics.

  • Stakeholder Interviews: Collaborated with healthcare professionals to understand diagnostic workflows and information gaps.

  • Brainstorming Sessions: Ideated early concepts around user reassurance, accessibility, and trust-building.


Journey Map

My Design Process


Phase 1: Information Architecture

I began by mapping the core user journeys - the structure prioritized quick access to critical tools (like tick ID, symptom checker, and bite log) while ensuring secondary features supported user confidence and learning.

  • Scan : Identify tick species using AI.

  • Health Tracker: Log bites and monitor symptoms.

  • Insights: Visualize regional and seasonal patterns.

  • Learn – Browse educational resources.

Phase 2: Wireframes & User flows

I explored different layouts for image uploads, results pages, and symptom logging — testing how users interpret feedback and what level of guidance felt most reassuring.

Through multiple iterations, I refined navigation patterns and interaction elements to create a seamless, trustworthy flow — one that balances clarity, empathy, and data accuracy.


Phase 3: Prototyping & Validation

I created interactive prototypes and tested them with users and healthcare professionals.

  • Observed how users navigated critical paths like tick ID, symptom tracking, and education access.

  • Employed minimal typography and gentle motion to guide users subtly.

  • Added micro-interactions to build trust — small, meaningful feedback moments that reassured users their actions were recognized.


Solution Design

After validating the information architecture through low-fidelity wireframes, I translated user needs and research insights into polished, interactive screens. These high-fidelity prototypes demonstrate the complete user journey with production-ready visual design.


Core User Flows


Future Design Challenges

Designing AcuTick AI involved balancing medical accuracy, usability, and user trust, all under conditions where users might feel anxious or uncertain. Several unique challenges emerged during the process:

Notifications and reminders are essential for tracking bites and symptoms, but too many alerts could cause anxiety or be ignored altogether. Finding the right balance — gentle, timely, and customizable — became a key focus.


Another challenge was making the app work for users offline. Many tick bites occur in parks, forests, or rural areas where connectivity is limited. There was a need for a system that allows users to log bite locations and access risk maps even when there’s no internet, syncing data seamlessly when connectivity returns.


At the same time, we recognized that health professionals needed a parallel experience. Doctors and nurses require similar workflows but with additional complexity — multi-patient tracking, data analysis, and pattern recognition. Designing a flow that felt familiar yet powerful for professionals was a delicate balancing act.


Finally, there was the challenge of handling multiple images. Users often take several photos of ticks or bites to track changes over time or for identification purposes. We needed a way for users to upload multiple images easily, with previews and clear instructions, so tracking bites would be simple and accurate.


Designing AcuTick AI involved balancing medical accuracy, usability, and user trust, all under conditions where users might feel anxious or uncertain. Several unique challenges emerged during the process:

Notifications and reminders are essential for tracking bites and symptoms, but too many alerts could cause anxiety or be ignored altogether. Finding the right balance — gentle, timely, and customizable — became a key focus.


Another challenge was making the app work for users offline. Many tick bites occur in parks, forests, or rural areas where connectivity is limited. There was a need for a system that allows users to log bite locations and access risk maps even when there’s no internet, syncing data seamlessly when connectivity returns.


At the same time, we recognized that health professionals needed a parallel experience. Doctors and nurses require similar workflows but with additional complexity — multi-patient tracking, data analysis, and pattern recognition. Designing a flow that felt familiar yet powerful for professionals was a delicate balancing act.


Finally, there was the challenge of handling multiple images. Users often take several photos of ticks or bites to track changes over time or for identification purposes. We needed a way for users to upload multiple images easily, with previews and clear instructions, so tracking bites would be simple and accurate.


Designing AcuTick AI involved balancing medical accuracy, usability, and user trust, all under conditions where users might feel anxious or uncertain. Several unique challenges emerged during the process:

Notifications and reminders are essential for tracking bites and symptoms, but too many alerts could cause anxiety or be ignored altogether. Finding the right balance — gentle, timely, and customizable — became a key focus.


Another challenge was making the app work for users offline. Many tick bites occur in parks, forests, or rural areas where connectivity is limited. There was a need for a system that allows users to log bite locations and access risk maps even when there’s no internet, syncing data seamlessly when connectivity returns.


At the same time, we recognized that health professionals needed a parallel experience. Doctors and nurses require similar workflows but with additional complexity — multi-patient tracking, data analysis, and pattern recognition. Designing a flow that felt familiar yet powerful for professionals was a delicate balancing act.


Finally, there was the challenge of handling multiple images. Users often take several photos of ticks or bites to track changes over time or for identification purposes. We needed a way for users to upload multiple images easily, with previews and clear instructions, so tracking bites would be simple and accurate.


Project Impacts

By combining AI technology with industry tick surveillance data, we created a solution that reduced identification time by 87% and helped users get timely medical care.