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 #7,010 place in the like-ranked listing is a tie-break inside that group, not a ranking.
Projects (log scale)
Likes on Devpost. ▲ marks this project's group.
Show the figures
| Likes | Projects | Share of archive |
|---|---|---|
| 0 | 5,592 | 71.2% |
| 1 | 1,758 | 22.4% |
| 2 | 285 | 3.6% |
| 3–4 | 132 | 1.7% |
| 5–9 | 75 | 1.0% |
| 10+ | 14 | 0.2% |
Executive Summary
What the company appears to be
StudentLink AI is a self-reported AI-powered platform aiming to help students and alumni discover people, opportunities, and connections globally. It was submitted as a project to the OpenAI 2026 hackathon by one founder, Raghav Jain.
What changed
No evidence of prior existence or development; this is a new submission to a hackathon.
The single most important open question
Is there any evidence that StudentLink AI has traction, revenue, or even a functional prototype beyond the hackathon submission?
What The Product Actually Is
The description states: “A global AI-powered network helping students and alumni discover the right people, opportunities, and connections.”
- Inferred: The product is described as an AI-powered platform or network.
- Not evidenced: No details on how it works, what data it uses, or whether it’s a web app, mobile app, or API.
Evidence
- Tagline: “A global AI-powered network helping students and alumni discover the right people, opportunities, and connections.”
- Built with: codex, gpt-5.6, openai, react
- Submitted to OpenAI 2026 hackathon
Positioning & Claim Evolution
The description states: “A global AI-powered network helping students and alumni discover the right people, opportunities, and connections.”
- Claim: The platform is positioned as a global network for student/alumni discovery.
- Not evidenced: No indication of how this differs from existing platforms (e.g., LinkedIn, alumni networks), or whether it has evolved from an earlier version.
Evidence
- Tagline
- Submission to hackathon
Target Customer & ICP
The description states: “helping students and alumni discover the right people, opportunities, and connections.”
- Claim: The primary users are students and alumni.
- Not evidenced: No segmentation, user personas, or targeting strategy.
Evidence
- Tagline mentions students and alumni
- No further detail
Business Model & Pricing Evidence
The description states nothing about pricing or monetization.
- Not evidenced: No mention of revenue model, pricing tiers, or monetization strategy.
Evidence
- No information provided
Technical & Delivery Signals
The description states: “Built with (author-declared): codex, gpt-5.6, openai, react”
- Inferred: The platform uses AI models (GPT) and a React frontend.
- Not evidenced: No details on architecture, scalability, or delivery mechanism.
Evidence
- Built with: codex, gpt-5.6, openai, react
Traction & Maturity Signals
The description states: “This project was submitted to the OpenAI 2026 hackathon.”
- Inferred: The product is in early development or prototype stage.
- Not evidenced: No evidence of users, adoption, or traction beyond a hackathon submission.
Evidence
- Submitted to OpenAI 2026 hackathon
- Team size: 1
Competitive Context
The description states nothing about competitors.
- Not evidenced: No mention of existing platforms in this space (e.g., LinkedIn, alumni networks, student platforms).
Evidence
- No information provided
Key Risks & Red Flags
- Risk: The project is a hackathon submission with no prior traction or product development.
- Red Flag: One-person team with no evidence of execution or market validation.
- Not evidenced: No indication of user feedback, product-market fit, or scalability.
Evidence
- Submitted to hackathon
- Team size: 1
Diligence Questions To Ask The Founders
- What is the core problem you are solving for students and alumni?
- How does your platform differ from existing tools like LinkedIn or university alumni networks?
- Have you validated your idea with any users or early adopters?
- What is your plan to scale beyond a hackathon prototype?
- Are there any existing partnerships or pilot programs?
Investment/Partnership Verdict
Not evidenced: No evidence of revenue, traction, or business model.
- Inferred: This is an early-stage idea submitted to a hackathon.
- Confidence level: Very low — this is a self-reported, unverified concept with no demonstrated progress.
Evidence
- Submitted to OpenAI 2026 hackathon
- No prior product or user data
- One founder, no team or funding evidence
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.