AllorAI
December 2025 - February 2026
AllorAI is a travel planning application featuring a specialized AI agent that generates personalized itineraries. The platform streamlines the planning process by tailoring travel suggestions to each user's unique interests and preferences.
This is my first time working on a Hackathon project and it's got me nervous but excited. The Hackathon is held by Gridiron Survivor, an apprenticeship program that equips self-taught designers and developers with essential work experience to help them succeed in tech. The Hackathon also has sponsors that include GitKraken, Frontend Mentor, and Zephyr Cloud. Throughout the Hackathon, live presentations are hosted where the teams share their progress and insights through sprint demos. With sponsors, people watching, and a limited amount of time, the pressure is definitely on. Despite my anxiety, I persevered through this Hackathon and rose to the challenge of designing an intuitive AI desktop application.
Note: AllorAI was developed specifically for desktop.
Team
Bradley Diep | Designer
Monica Shin | Designer
Tony Briely | Developer
Jeremy Fischer | Developer
Hector Suazo | Developer
My Role
UX/UI Design
Research
Tools
Figma
FigJam
Adobe Illustrator
Google Workspace
Figma MCP
Visual Studio Code
Research
Problem
How do we design a desktop app with an AI travel agent that helps users build their own itinerary?
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Users are generally hesitant to let AI take control of their travel plans because of the lack of transparency in its recommendations.
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Planning a trip is a high-stakes financial and emotional investment.
Goal
What do we accomplish through this project?
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Make the AI feel like a competent human assistant rather than just a "search bar with a personality".
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Guide the user through one decision at a time and prioritize the user's subjective preferences.
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Alleviate the stress of trip planning.
Pain Points
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Planning Becomes a Chore: Even with AI tools, travelers often find themselves with dozens of open tabs trying to check flight prices and cross-referencing hotels to stay at. The process of planning a trip feels like a part-time job rather than something exciting to look forward to.
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Outdated Logistics: AI might confidently suggest a location to travelers that may actually be under construction, closed for years, or much more costly than anticipated.
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Algorithmic Funneling: AI tends to recommend the most "popular" spots because they appear most frequently in its training data, which means travelers can miss out on some amazing experiences and "hidden gems".
Competitor Analysis
Before designing, we conducted a competitor analysis on other travel applications to identify their advantages, disadvantages, and notable features that could inspire us in the project.
After researching our competitors, we decided that our app should focus on balancing AI integration with user agency. Therefore, we needed to design where and how much AI would be involved in the trip-planning process. Our goal was to ensure the AI assists rather than dictates, while providing transparent, budget-conscious options that adapt to each traveler's unique priorities.
Early Designs
Low-fidelity Designs
With my fellow designer, Monica, we ideated and sketched various interface concepts to define the app’s visual and functional direction.
Mid-fidelity Designs
After synthesizing our initial sketches into mid-fidelity wireframes in Figma, we met up with the developers on our team to evaluate technical feasibility. The discussions we had regarding scope and resource constraints led us to prioritize a Minimum Viable Product (MVP) focused on a core user flow: planning a simplified trip with the assistance of Allora, our AI chatbot. By iterating closely with the developers, we balanced our creative goals with functional limitations to establish a structural foundation for AllorAI.
The following wireframes represent our refined iterations, showcasing the final structural decisions before moving into high-fidelity design.
Landing Page
Selling Points:
The 3 card components on the landing page display reasons why users should consider using AllorAI.
Input Form:
Below the selling points is an input form that helps narrow down the trip-planning process by having users input important parts of their trip like the destination and dates.
Chatting with Allora
Once users submit their input form, they will begin chatting with Allora to determine their trip budget priorities. Allora acts as the principle travel agent that helps users plan their trip step-by-step. By emulating text conversations, Allora is positioned as an assistant.
Allora:
On the left side of the chat, Allora summarizes the users' choices and instructs them on next steps.
The Users:
On the right side of the chat, users select choices on flights, lodging, and other preferences based on what they want to focus their budget on.
Selecting Experiences
When users are finished planning their flights, lodging, and trip budget, they'll move on to planning the rest of their trip by selecting experiences they want to encounter.
Experience Filters:
Users can click on different filters to see specific experiences rather than all the results.
Experience Cards:
Showcase general information on each experience in a condensed but briefly informative format.
Budget Overview:
Helps users keep track of what they’re spending on (flights, hotels, pinned experiences).
Travel Tips:
Allora provides information about the destination for additional knowledge and precautions.
Logo Design
Logo Design Process
I used Google Gemini to get inspiration for a couple logo ideas to define the branding of AllorAI.
Prompt:
“Generate different versions of a logo named Allora AI".
Prompt:
“Make the logos have a travel theme".
From the logos that were generated, I decided to choose the one on the top right as the basis for AllorAI's logo and created some variations in Adobe Illustrator.
AI-Generated Logo Choice
AllorAI Logo Variations
AllorAI Logo (Final Version)
To reinforce the brand’s travel identity, the final logo features a plane flying around a globe. By blending terrestrial tones of blue and green with a dynamic gradient, the design evokes a sense of world exploration and high-tech sophistication to mirror the 'intelligence' of a modern AI assistant.
Final Designs
Style Guide
We extended the logo’s color palette throughout the UI and paired it with minimalist sans-serif typefaces. This combination establishes a modern, high-tech aesthetic that aligns with the AI-driven nature of the platform.
Header Typeface
Montserrat
Body Typeface
Figtree
High-fidelity Designs
While the two screens above remained functionally consistent with previous iterations, other screens underwent significant refinements, and additional screens were added to better support the user journey.
Allora Chat Messages
To provide clear visual cues during the chat, we implemented state-driven colors: previous messages transition to indigo, while active prompts are highlighted in turquoise to show that they are interactive.
Selecting Experiences from Filters to Tabs
Why the Tab Change:
To streamline the browsing experience, we transitioned from filter buttons to a categorized tab system. This provides a much cleaner interface for discovering experiences, making the options feel organized rather than overwhelming.
Tab Counter:
To provide immediate visual confirmation, each tab includes a dynamic counter. When a user pins an experience card, the corresponding tab reflects the selection in real-time (Ex: Activities 1). This serves as a reminder of their choices and ensures all selections are automatically synced with the budget overview.
Review Page
Upon completing the trip-planning process, users are directed to the Review Page. After entering a custom name for their trip, they are presented with a detailed summary of their selections. This serves as a vital validation step, ensuring every selection perfectly aligns with their travel goals and budget.
Saved Trips Page
By logging in, users can view their saved trips. Each trip is easily identified through key metadata, including a cover image, trip title, travel dates, and the original planning date. To maintain focus on the MVP, advanced features like editing and sharing remain as planned future enhancements.
Note: The high-fidelity designs shown in this section are not entirely accurate to the final product. Additionally, AllorAI was developed specifically for desktop.
More Info Soon