AITou
Helping international candidates make high-stakes job decisions with AI, data, and trust
My Role: Founding Product Designer, Product Manager
Team: 1 Designer, 3 Engineers
Tools: Figma, ChatGPT
Duration: ~5 Months, from scratch to launch
Problem
International job seekers make high-stakes decisions during their job search.
Unlike domestic candidates, H1B and OPT applicants must evaluate sponsorship likelihood, company history, and visa risk — often without reliable or complete information.
Critical signals are scattered across government datasets, job boards, and community sources, turning job decisions into a slow, stressful, and error-prone process.
Opportunity
How might we help international candidates make confident, informed job decisions in an environment defined by uncertainty and information asymmetry?
Goals & Success Metrics
Help international job seekers make more confident, informed job decisions by reducing uncertainty around sponsorship, company history, and visa risk.
Improve job search efficiency by surfacing decision-critical signals at the right moment in the workflow, reducing time spent on manual research across fragmented sources.
Drive sustained product usage during active job search periods by becoming a trusted decision-support tool rather than a one-time lookup utility.
Key Hypothesis
Clearly surfacing sponsorship likelihood and company history will increase candidate confidence and repeat usage.
Synthesizing fragmented data into decision-ready insights will reduce research time and accelerate action.
Context-aware interview preparation will increase perceived value and sustained engagement throughout the job search.
Measured Impact
Chrome Web Store
DAU
2000+
Job Posts Analyzed
2M+
Discovery
Decision Support
Decide Where to Apply, at a Glance
For our users, simpler is better
The goal is to develop a tool that simplifies and enhances the job-hunting process for international candidates, making it easier for them to secure meaningful employment and advance in their careers.
For international job seekers, job searching isn’t just about finding roles — it’s about managing risk.
We began by considering what matters most to our users during their job search.
The answer is 'Visa Sponsorship'.
For our business, we need user expansion
AiTou already has an established brand as a job-seeking and referral platform. However, due to the significant layoffs in the tech industry, fewer people are using the referral program. We aim to create an entry point to attract new users and expand our user base.
We aim to identify job seekers' pain points and provide solutions with a minimal learning curve.
Quickly accumulate users and direct them to our main domain.
New users can discover existing features on our website, driving business expansion.
Make application decisions at a glance
Verified sponsorship badges appear directly in LinkedIn job listings, helping candidates quickly decide which roles are worth applying to.
To preserve a seamless browsing experience, the extension matches LinkedIn’s native UI and typography.
Dark mode, built in
Supports LinkedIn’s dark mode for a more comfortable job search experience.
No dead ends, even with missing data
When no sponsorship data is available, users can report inaccuracies directly from the job listing. This ensures candidates are never blocked by missing information.
User feedback becomes part of the data loop, improving accuracy while keeping maintenance scalable.
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H-1B Sponsorship
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Decision-Ready Tooltips
Inline tooltips clarify critical sponsorship signals at the moment of discovery, helping users quickly assess eligibility without leaving the job listing.
Data sources are clearly attributed to USCIS, reinforcing trust and confidence in every decision.
Retention
Activation
Never Miss the Right Opportunity
A personalized dashboard that surfaces relevant, newly posted roles as soon as they appear.
Timing matters in a competitive job market.
The dashboard highlights new opportunities based on user preferences, helping candidates act quickly and focus on roles that matter most.
Information Architecture Behind the Design
From Signal to Confidence
When a role passes the initial filter, users can click directly into a detailed view of the company’s sponsorship history.
This allows candidates to validate signals, understand patterns, and decide whether a role is worth pursuing further.
Explore Sponsoring Companies
Users can dive deeper into company-level sponsorship data to validate and compare opportunities.
Retention
Conversion
Turn Intent Into Completed Applications
Many job seekers drop off before applying - not because of the role, but because repetitive writing slows them down and adds uncertainty.
This tool removes friction at the final step, helping users generate tailored cover letters and prepare interviews in one flow — turning intent into confident applications and repeat usage.
Structured Interview Practice, Not Guesswork
Interview preparation is often unstructured — users don’t know what to practice, how to improve, or whether they’re making progress.
By adapting to each user’s role and performance, the interview assistant delivers targeted questions and feedback at the right time, helping users practice with clarity and purpose.
Actionable Interview Feedback
Instead of generic AI chat, the Interview Report focuses on what actually went wrong — and what to improve next.
Performance is broken down into clear signals such as communication clarity, structure, and word choice, allowing users to spot patterns, track progress, and improve with intention over time.
Interview Progress, Clearly Tracked
Interview preparation is rarely linear. Users need visibility into what they’ve completed, where they left off, and what still needs work.
The interview dashboard helps users manage sessions over time, resume unfinished interviews, and build consistent practice habits instead of starting from scratch.
Reflection
This project was shaped by real constraints, a competitive job market, limited resources, and high-stakes user decisions.
Working on AITou pushed me to think beyond interface design and focus on end-to-end product problem solving. I broke down complex, ambiguous challenges into smaller, testable decisions, balancing user needs with business realities throughout the process.
With limited resources, I took on responsibilities beyond design, including product scoping, prioritization, and lightweight research. This experience strengthened my ability to operate across product, design, and strategy, and reinforced how much I value building practical solutions that can ship and scale.
Looking Ahead
Although the product was eventually paused due to funding constraints, it successfully supported thousands of users during an especially challenging hiring cycle.
The learnings from AITou continue to shape how I approach product design, focusing on clarity, decision-making, and building systems that remain valuable even under uncertainty.
AITou reinforced how much I value designing systems that help people make better decisions under uncertainty, a principle I continue to carry into every product I build.
