OpenAI 2026 hackathon

ScholarshipHub

ScholarshipHub helps students track applications to scholarships like Chevening, Fulbright, and Erasmus, allowing them to effectively manages deadlines, documents, and progress all in one place.

Solo project by Liu Yang · 0 likes · 0 comments

Archive position — measured, not model output

0 likes on Devpost

2,264 of the 7,856 archived projects have more likes, and 5,592 share exactly 0 — so this project's #6,568 place in the like-ranked listing is a tie-break inside that group, not a ranking.

Projects (log scale)

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Likes on Devpost. ▲ marks this project's group.

Show the figures
LikesProjectsShare of archive
05,59271.2%
11,75822.4%
22853.6%
3–41321.7%
5–9751.0%
10+140.2%
Devpost like counts for all 7,856 archived projects, captured when this archive was built.

Executive Summary

Project: ScholarshipHub

Self-reported basis: The analysis is based entirely on the author's own description of ScholarshipHub, submitted as part of a Devpost hackathon entry. No external verification or independent sources are available.

Confidence level: Low — this is a self-reported project with no evidence of traction, revenue, customers, or funding.

Key finding: The product appears to be a personal project built by one developer to solve a personal problem, with no clear commercialization strategy or evidence of adoption beyond the author’s own claim of “first paid users” just two days after publishing.

Most important open question: Is there any evidence that this tool has been adopted by students beyond the author's own use and initial paid users?

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What The Product Actually Is

The description states that ScholarshipHub is an application tracker for Vietnamese students applying to international scholarships such as Chevening, Fulbright, Erasmus Mundus, and others. It centralizes deadlines, required documents, and application progress in a single dashboard.

  • Inferred: The tool is built to help students manage scholarship applications more efficiently.
  • Not evidenced: Whether the tool actually functions beyond a prototype or has been used by students other than the author.

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Positioning & Claim Evolution

The author states that ScholarshipHub was inspired by their own experience of losing track of scholarship application information across multiple platforms. The product is positioned as a solution to this problem, aiming to help students apply on time and with proper preparation.

  • Claim: The tool helps students manage deadlines, documents, and progress for multiple scholarship programs.
  • Inferred: It is intended to be a personal productivity tool for students applying to international scholarships.
  • Not evidenced: Whether the product has evolved beyond its initial idea or if there are plans to scale it into a service.

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Target Customer & ICP

The author states that ScholarshipHub is built for Vietnamese students applying to top international scholarships such as Chevening, Fulbright, Erasmus Mundus, and others.

  • Claim: The target customer is Vietnamese students.
  • Inferred: The tool is tailored to the needs of students applying to specific scholarship programs.
  • Not evidenced: Whether the tool has been adopted by students beyond the author’s own use or whether there is a defined ICP beyond the initial user base.

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Business Model & Pricing Evidence

The description states that the author “got my very first paid users just two days after publishing,” but does not provide any details on pricing, monetization strategy, or business model.

  • Claim: There are paid users.
  • Inferred: The product may be monetized through subscriptions or one-time purchases.
  • Not evidenced: No pricing information, revenue model, or customer acquisition costs are provided.

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Technical & Delivery Signals

The author built the tool solo using a dual-agent AI workflow involving Claude Code and OpenAI Codex. They also used various technologies including Node.js, Express.js, SQLite, PostgreSQL, JWT, Google OAuth, Sentry, and more.

  • Claim: The product was built with AI assistance.
  • Inferred: The tool is technically functional, though not necessarily scalable or production-ready.
  • Not evidenced: No information on deployment infrastructure, scalability, or technical architecture beyond the tools used.

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Traction & Maturity Signals

The author claims to have “got my very first paid users just two days after publishing.” They also state that they are still improving the web app and working on increasing its presence among applicants.

  • Claim: There are early adopters and paid users.
  • Inferred: The project is in an early stage of development with limited traction.
  • Not evidenced: No data on user growth, retention, or engagement. No evidence of a sustainable product-market fit.

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Competitive Context

The author does not mention any competitors or existing tools for tracking scholarship applications. However, the idea of centralizing scholarship application information is not unique — there are likely existing platforms or tools in this space.

  • Inferred: The market may be crowded with similar tools.
  • Not evidenced: No competitive analysis, pricing, or differentiation strategy is provided.

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Key Risks & Red Flags

  • Single-founder project: The tool was built by one person, which raises concerns about scalability and long-term maintenance.
  • No commercial traction: There is no evidence of revenue, customers, or adoption beyond the author’s own use and early paid users.
  • Unverified claims: All claims are self-reported and unverified — including the existence of paid users.
  • Lack of product-market fit evidence: No data on user behavior, retention, or engagement.

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Diligence Questions To Ask The Founders

  1. What is the actual number of users, and how many of them are paying?
  2. How do you plan to scale beyond a single developer?
  3. What is your monetization strategy beyond early paid users?
  4. Are there any existing tools in this space that you’re competing with or differentiating from?
  5. How do you intend to acquire more students beyond the initial user base?

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Investment/Partnership Verdict

Not evidenced: There is no evidence of a viable business model, revenue, or customer traction to support an investment or partnership decision.

  • Inferred: The project is in an early stage and may have potential if it can scale beyond its current scope.
  • Confidence level: Very low — this is a self-reported personal project with no external validation or evidence of commercial viability.

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Source

Submitted to the OpenAI 2026 hackathon on Devpost. Project home on DevPost.

The analysis above was generated by a language model from the project's own one-line description. It is not independent research and contains no verified traction, revenue or customer data.