AI workspace streamlining team productivity
AI Interaction
B2C · SaaS
Overview
I led the research and UX strategy for LABO, an AI‑powered collaboration tool designed to eliminate inefficiencies in team workflows. I applied diverse UX methodologies to transform user insights into actionable solutions, developing high‑fidelity prototypes and an iterative design system that optimized team productivity. By integrating automation, task management, and real‑time insights, LABO streamlined collaboration and reduced communication gaps.
Role
Product Designer
Team
4 Product Designers
Sponsored company (MMG)
Responsibilities
UX Design
UX Research
Usability Testing
Timeline
3 Months
🏆
LABO ranked 1st Place in Strategic Innovation in Product & Service Design class
(by professors and sponsors)
Why we started?
“We often find ourselves tangled in a web of inefficient project management and communication, leading to wasted time, rising costs, and missed opportunities for growth.”
— CEO, Motivated Mind Group
Challenge
Teams struggled with fragmented communication and repetitive tasks, causing inefficiency and slower progress.
Opportunity
Enhance cross‑team communication and workflow efficiency through AI‑driven task management, real‑time insights, and contextual automation.
Solution
1. Users can see their task at-a-glance
2. Information obtained quickly through suggestions
3. Users can experience seamless AI usage by simply dragging
Evaluation
To evaluate the final design, we conducted a task-based usability test with 8 of IT industry employees.
Sucess rate
%
Sucess rate
/ 5
Journey to find an answer
Design Process
HMW question
How might we intelligently assist teams to come together seamlessly, collaborate effortlessly, and boost productivity?
Why is matter?
Inefficient communication and poor teamwork are costing businesses time and money.
72%
of business leaders faced communication issues, impacting collaboration.
$537B
Poor teamwork leads to $537B in annual losses for U.S. businesses.
6Hrs
of employees waste 6 hrs/wk searching for info due to poor communication.
Research & Problem
Through 33 interviews and data collection…
I realized how fragmented communication and repetitive tasks directly hinder team productivity.
Fragmented communication causes information gaps, leading to team confusion and misunderstandings.
Juggling multiple projects makes it hard to stay focused, slowing down progress and lowering efficiency.
Repetitive tasks and organizing records take time away from important work.
Design
Conducted quick usability testing on early-stage wireframes to validate content hierarchy and feature placement before visual design. This rapid feedback loop allowed for faster, more informed design decisions while keeping the process user-centered and efficient.
Iteration
After designing the wireframe…
Through A/B and user testing, I identified usability gaps and refined the design to better align with users.
Scaling Product
Takeaway
User-Centered Iteration, Data-Driven Design
Through extensive user interviews and A/B testing, we uncovered gaps between user expectations and initial designs. Iterative feedback loops and diverse testing revealed how AI could streamline workflows while remaining intuitive. By combining deep research insights with data-driven tools, we created a product that resonated with real user needs and behaviors
Next Project
New Jersey AI Assistant
Redesigning AI assistant for 64K government workers
Civic Tech · AI
Usability Testing
Role
Product Design Intern
Team
2 Product Designers 1 Project Manager 2 Front-end Engineers
Timeline
3 Months
My Contribution
Led UX research & interviews, translating insights into AI-driven design solutions.
Refined workflows through data-driven iteration, improving accessibility & automation.
Developed high-fidelity prototypes to streamline AI interactions & enhance usability.
Collaborated with engineers & PMs to align AI capabilities with user needs.
Overview
As a Product Design Intern at NJ OOI, I led a Stretch Project to enhance NJ AI Assistant, an internal AI tool supporting 64,000 public employees. Over 4-5 weeks, I tackled inefficiencies, improved workflows, and refined the user experience.
Problem
Interruptions and Inefficiencies
Frequent timeouts and the absence of chat history disrupted user workflows, causing repetitive tasks and reducing productivity. Additionally, limited text-input functionality and restricted file support hindered user satisfaction.
Key findings
57.7%
of users identified
the lack of chat history
as a critical issue.
65%
requested expanded
file type support for
formats like CSV and PDF.
34%
highlighted the need for
work-specific
templates to streamline tasks.
How might we enhance NJ AI Assistant to create a more
seamless experience while reducing repetitive tasks?
Design Solution
Chat History
Problem
Insight
Users are frustrated by losing work and repeating inputs due to session timeouts and lost context.
57.7% of users identified this as a severe issue.
Preserving session data and chat history improves workflow continuity and reduces repetitive tasks.
Enhanced Text Input
Problem
Insight
1. Small text-input size limits content review.
2. Current system cannot handle additional file types.
65% of users requested expanded file support.
Enhancing flexibility and expand file support will improve workflow and user satisfaction.
Work Templates
Problem
Insight
Users struggle with creating effective prompts, wasting time on repetitive tasks due to a lack of predefined templates.
34% of users requested templates relevant to their use cases.
Providing pre-made templates simplifies workflows, reduces the learning curve, and improves usability for new users.
Template in input-text
Select Tone
Feedback or Impact
Feedback
“Very clean and intuitive designs!”
so impactful for turning the insights from user research into product)
Impact
The improved NJ AI Assistant addressed key user frustrations:
Chat history enhanced workflow continuity.
Expanded text input and file support boosted usability and satisfaction.
Templates reduced the learning curve for new users.
Short-term outcomes included usability testing and
Takeaway
Through this project, I deepened my expertise in designing for AI-driven tools and learned to prioritize effectively using data-driven methods. Leading this project solo strengthened my ability to manage end-to-end design processes under time and resource constraints, while aligning with cross-functional teams.