UX Design Internship
Chai (formerly ChaiOne)
From supporting UX flows to my first client project - delivering scalable enterprise UX through real-world collaboration.
TIMELINE
Sep 2021 - Jan 2022
TEAM
Andy Shaffer (Manager)
Osama Ashawa (Lead)
Rick Carruth (Senior)
Bonita McBride (Mentor)
Amy Yow (Behavioral Sc)
MY ROLE
UX Design Intern
TOOLS
Figma, Miro, Microsoft Teams, Word, PowerPoint, Excel
Summary
This internship didn’t start with a job description. It started with initiative.
During my final semester in the MS HCID program, I reached out to a contact at ChaiOne to ask for hands-on experience. There was no formal opening, but they welcomed me to join the design team as an intern and that open-ended start became one of the most formative learning experiences I’ve had.
I began as a UX intern in September 2024 and extended my time at ChaiOne after graduating. What started as a 3-month internship grew into an extended contract through mid-2025.
Before I continue, please meet the incredibly talented team at Chai!
WHAT I WORKED ON
1. Design Flows for a Client-Facing Product
My primary task was supporting my lead designer, Andy, on a client product. I was responsible for building high-fidelity design flows based on previous examples, guidance from Andy, and our internal design library. I worked to:
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Translate narrative stories into annotated design flows
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Apply an existing (and very large) design system with precision
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Ensure each flow was ready for developer handoff with descriptions and annotations
This was my first time working with an enterprise-level design library, and it pushed me to become more efficient, consistent, and systems-oriented.
-> Due to NDA constraints, I can’t share the product name, but it has since launched.
WHAT I WORKED ON
2. Supporting ChaiOne’s AI Pivot
As ChaiOne expanded its enterprise offerings into AI, I was embedded in early design initiatives that explored how AI could solve real client pain points.
Context
ChaiOne, a B2B product and services company focused on energy and logistics, began pivoting toward AI-centered solutions in 2024. I joined as a UX Design Intern during this critical transition, contributing to both client-facing strategy and internal product design.
My Role
Collaborated with Amy, our behavioral scientist and in-house AI lead, to design Agentic AI Canvas and interactive workshop boards. These tools helped clients identify viable AI use cases aligned with their business challenges.
Contributed to the strategy decks now used by our sales and consulting teams to position ChaiOne’s AI services to prospective clients.
Worked cross-functionally with UX leads, BAs, and engineers to ensure edge-case handling, systems alignment, and handoff clarity.
Designed UX flows for a computer vision agent that detects visual damage in trucks and equipment. This product is now expanding to include other asset types across logistics and field operations.
Impact
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The AI canvases and decks I contributed to are now published publicly on ChaiOne’s website and are used in live AI strategy workshops.
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My work helped translate abstract AI capabilities into tangible value for clients — anchoring the product vision in real user pain points.
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I gained firsthand experience in integrating AI concepts into enterprise UX workflows, while building scalable documentation and flows.
My Projects
Truck Damage Vision Agent
Mobile App
I contributed to the design of a mobile capture flow that enables users to take structured photos of vehicles after an accident. The AI vision agent uses these images to detect external damage and identify assessment needs.
Design Highlights ✨
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Empathetic microcopy (“Perfect! You have successfully uploaded...”) helps humanize the process after a potentially stressful incident.
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Visual mapping of detected damage enables intuitive understanding, without overwhelming the user with technical jargon.
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Modular and scalable: This flow was designed to accommodate additional asset types beyond trucks — including heavy equipment, fleet vehicles, and more
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The user is prompted to begin with the front view of the vehicle. A simple visual guide establishes expectations and reinforces the goal of collecting complete image data for accurate AI assessment.
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As the user positions their camera, the vision agent analyzes the live feed. If the image lacks key visual coverage (e.g. bumper not visible), the interface provides immediate guidance to help the user adjust.
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When the image meets required criteria (e.g. clarity, alignment), the frame turns green and prompts the user to capture the photo. This reinforces a sense of progress and reduces cognitive load.
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Once a photo meets the quality requirements, the system confirms successful upload for each view. Users are reassured with clear visual feedback, and given the option to retake if needed, maintaining control throughout the process.
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After uploading all required views (e.g., front, driver side, back), users review their image set before submitting for AI-based analysis. The interface keeps cognitive load low by showing visual confirmation for all completed angles.
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The AI analyzes each image and provides a clear visual summary of detected issues. Areas with potential damage are flagged with color-coded markers and severity indicators.
Equipment Damage Vision Agent
Web
In parallel with designing mobile flows for image capture and AI-assisted damage detection, I also contributed to high-fidelity mockups for a web-based AI operations dashboard. This dashboard allows field operators and analysts to review, verify, and act on AI-detected issues across industrial sites.
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To support high-volume operations, the platform includes a dynamic table that lists all open, escalated, or resolved issues. Users can sort by severity, detection source (drone, CCTV, sensor, etc.), confidence level, or status. Color-coded tags improve scan-ability across 240+ concurrent incidents.
2/
The system flags a generator showing signs of overheating, detected via drone input. A bounding box appears over the area of concern, along with a 90% confidence score. The interface surfaces supporting context: site location, detection time, and device source. Users can immediately escalate, create a work order, or mark the issue as a false positive.
WHAT I WORKED ON
3. Leading a New Client Project (Contract Role)
As my contract was extended, I was given the opportunity to lead a new project as a contract UX designer—designing a mobile booking experience for a luxury charter flight company. I scoped the user flow, drafted early wireframes, and prepared internal documentation. While the project is currently on hold due to external factors, this experience gave me the chance to practice design leadership and early-stage client collaboration.
WHAT I LEARNED
1. Communication is Everything
Sitting in on team meetings taught me how miscommunication leads to repeated problems, missed requirements, and tension across teams. It also showed me how much more effective designers are when they understand what happens before and after their work enters the pipeline.
2. Design Needs Business Awareness
I saw firsthand that not all projects have the budget or scope for research—and the projects that do usually get better results. That helped me reframe how I think about research not just as a UX best practice, but as a business investment.
Outcomes
Impact on the business
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Contributed production-ready flows now part of a launched enterprise product
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Helped create internal and public-facing AI resources used in business development
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Practiced rapid learning and design inside real-world constraints: limited research, tight timelines, shifting goals
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Led early exploration for a new client app project while learning to scope and communicate under uncertainty
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Saw how UX connects to both internal collaboration and external client relationships
Insight
At ChaiOne, I didn’t own an entire product. But I learned how to support one—and eventually, how to lead one. I learned to collaborate inside ambiguity, communicate clearly across roles, and build work that fits into a much larger strategy. I also saw the early stages of AI integration—and got to play a part in designing what’s next.
Journey Map
To explore this, I sketched early flows and created a journey map to provide a holistic view and to map out specific instances of pain points which can be translated into design opportunities.
What do you want to see next?
Designing a digital alternative for paper brochures and maps.
View the quick study
Designing a digital alternative for paper brochures and maps.
View the quick study