Japa AI

Moving abroad is a life-changing goal, but it's currently a full-time job. Japa AI Agent automates the entire process, from finding scholarships, drafting applications and document checklist.

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Inspiration

Moving abroad is a life-changing ambition, but the process is notoriously broken. It is a fragmented, year-long ordeal of manual research, bureaucratic nightmares, and "application fatigue." We realized that while the global talent pool is mobile, the infrastructure to help them move is stuck in the past. We built Japa AI to bridge this gap, serving as an intelligent, automated concierge that handles the heavy lifting—from opportunity discovery to document compliance—so dreamers can focus on their future rather than the paperwork.

What it does

Japa AI is an end-to-end relocation companion that automates the migration journey:

  • Intelligent Discovery: Aggregates scholarships, PhD programs, and skilled worker visas tailored to the user’s specific profile (grades, field, budget).
  • Auto-Application Engine: Drafts country-specific personal statements and customizes CVs to match international standards.
  • Compliance Tracker: A centralized dashboard that maps out required documents (IELTS, transcripts, police records) and tracks deadlines.
  • Proactive Alerts: Delivers a weekly, personalized digest of new opportunities and urgent upcoming deadlines.

How we built it

Our team of four—Edidiong, Mildred, Phillip, and Bolanle—utilized a modern AI-agent architecture:

  • Core Logic: Built using Python and [Insert Agent Framework, e.g., LangChain/CrewAI] to orchestrate tasks between search, drafting, and tracking.
  • AI Integration: Leveraged [Insert Model, e.g., GPT-4o or Claude 3.5 Sonnet] via API to handle document drafting and profile matching.
  • Data Sourcing: Integrated [Insert APIs/Scrapers, e.g., SerpApi or custom scrapers] to pull real-time scholarship and job data.
  • Frontend/Dashboard: Built with [Insert Tech, e.g., Next.js/Tailwind CSS] to provide a clean, stress-free user interface.
  • Database: [Insert Database, e.g., Supabase/Firebase] for secure storage of user profiles and application progress.

Challenges we ran into

  • Data Fragmentation: Finding a reliable way to normalize data across diverse sources (different countries have different scholarship requirements).
  • Context Window Management: Ensuring the AI maintained consistency when drafting multiple long-form personal statements for different programs.
  • Real-time Synchronization: Keeping the tracking dashboard accurate as deadlines shift and new opportunities are posted.

Accomplishments that we're proud of

  • The "One-Click" Workflow: We successfully built a pipeline where a user's background is transformed into a ready-to-send personal statement in seconds.
  • Cross-Functional Execution: Despite being a team of four, we managed to integrate complex search APIs with a personalized generative AI backend within the hackathon timeframe.
  • User-Centric Design: Creating a dashboard that transforms "relocation anxiety" into a simple, step-by-step checklist.

What we learned

We learned the power of AI Agent orchestration—moving from simply querying an LLM to building a multi-step agent that can perform complex, multi-day tasks in minutes. We also gained deep insight into the specific pain points of international applicants and how much value "automated compliance" provides in a high-stakes process.

What's next for Japa AI

  • Document Verification: Integrating OCR technology to automatically scan and verify transcripts and certificates.
  • Visa Guidance: Expanding our logic to include real-time visa policy updates for target countries.
  • Community Integration: Adding a peer-matching feature so users can connect with others applying to the same institutions.
  • Beta Launch: Scaling to a public MVP to help our first cohort of users secure their transition abroad.

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