Elevating the everyday by bridging advanced technology with intuitive human experiences.

[ Keywords: AI UX/UI Integration • Digital Twins Technology ]

The Whos.

I’m a designer with a Bachelor of Architecture (BAS) and years of experience as a private consultant working at the intersection of physical and digital spaces. My work spans UX/UI design, the development of digital twin technologies and full-scale creative direction. At the core, I believe that good design is all about creating thoughtful, human-centered solutions that facilitate connection and improve day-to-day experiences.

The Whats.

Project [ 01 ]

Project [ 02 ]

AI UX/UI PRODUCT DESIGN

PROJECT [ 01 ]

Case Study:

Search & Discovery App with ChatGPT Integration

Summary:
UX/UI design for a mobile app that reimagines how people discover new experiences. This case study showcases how the product merges conversational AI with a highly visual, organized interface. Through interactive user engagement, the app enables users to receive tailored recommendations and intuitively store information within custom collections.

Role: Primary Product Designer (UX + UI, concept development, AI integration)
Duration: January 2025 - Present
Team: Independent designer working directly with client.
Tools: Figma, Conceptual AI API ChatGPT

Product Overview:
The product is a search and discovery platform that helps users easily find, save and explore destinations, activities, and experiences tailored to their interests. With personalized recommendations and intuitive search features, it simplifies planning by connecting users to options tailored to their location, travel destinations, personal needs and preferences.

The Challenge

Current search and discovery platforms often overwhelm users with generic suggestions, and storing useful results can be fragmented across multiple apps. Existing tools tend to:

  • Deliver static search results with minimal personalization.

  • Lack a visually appealing, centralized space to revisit saved ideas.

  • Treat conversational search (chat) and content organization (UI) as separate, disconnected experiences.

The Opportunity

With conversational AI becoming more capable, I saw an opportunity to:

  • Create a context-aware recommendation engine that learns over time.

  • Merge the human-like understanding of AI with an intuitive, visual interface.

  • Let AI not only suggest options, but also act directly within the app — organizing and saving results for future use.

The user’s activity trains the AI model on the user’s interests and preferences . This data combined with the ChatGPT chat box functionality generates a comprehensive user profile for a highly-tailored app experience.

Research & Insights

Due to budget constraints, I adopted a lean research approach focused on competitive analysis and informal feedback from peers:

  • Competitive review: Analyzed 8 relevant search and discovery apps (including Google Maps, All Trails, and Pinterest) to identify strengths and pain points.

  • Informal feedback sessions: Shared early concepts with peers to gather impressions of usability and value.

From this, three core opportunity areas emerged:

Deliver hyper-
personalized recommendations that improve over time.

Provide a unified,
visually organized space
for recommendations.

Create a seamless
bridge between chat-
based discovery and
UI browsing.

While formal user testing has not yet been conducted, the design leverages established interaction patterns and clear hypotheses that can be validated in future iterations.

The Solution

Core Concept: An AI-powered assistant embedded directly into the app’s core functionality.

Profile Building: AI develops a rich understanding of user preferences (likes, dislikes, allergies, mood) through both chat inputs and in-app behaviours.

Learning Loop: AI updates its profile with each interaction, refining future suggestions.

This project demonstrates how conversational AI can evolve into an active, functional assistant within a digital product for an improved user experience. The concept has clear scalability into ChatGPT’s UX, allowing users to intuitively organize information through a dynamic verbal and visual interface.

Design Process:
My design process focused on generating rapid, iterative sketches to explore UI layouts and functionality concepts, quickly testing and refining ideas. From there, I move into high-fidelity wireframes and interactive prototypes in order to move into development.

DIGITAL TWINS TECHNOLOGY

PROJECT [ 02 ]

Digital Twins:

Pioneering Digital Twin Technology – CBR Project

Roles: Technologist & Design Professional (If Then Architecture Inc. & HOK)
Duration: May 2019 - January 2023
Team: CENTRUS Joint Venture
Tools & Technologies: Point Cloud Models, Photogrammetry, BIM Integration

Summary:
During my time working on the Centre Block Rehabilitation project (CBR), I was part of a team pioneering the use of advanced digital modelling as the foundation for future digital twin technology. Spanning two roles at two architecture firms, my work bridged technical development with design application, contributing to one of the first real-time implementations of this emerging technology in the industry.

Process & Innovation
As a Design Technologist, I worked on the creation of highly detailed models using point cloud scanning and photogrammetry. These models captured the project’s as-found conditions with extreme accuracy, becoming the building blocks for live-project models integrating the past, present and future states of the building.

When I later joined HOK as a Design Professional, I continued working with these same models, layering intervention states with final conditions. These models are currently being utilized to develop designs and manage coordination across disciplines.

These models are the first of their kind to test the application of digital twin technology. By bridging live-data points and AI we can generate an interactive technology that can monitor and manage building systems in real-time.

Highly-detailed interactive digital models were generated by capturing point cloud data via laser scans. These models were then used to create BIM tools utilized by multiple disciplines such as architects, engineers and historians. By layering live-data points and time-based interventions, the team created an early iteration digital twin. The above images showcase the on-site data collection process.

Renders created from the digital models layering the point cloud information, photogrammetry and new design interventions.

Emily Lalonde

End of Portfolio.