OpenAI 2026 hackathon

femAI

FemAI is a privacy-first menstrual wellness app that helps users track cycles, symptoms, and mood while providing safe AI-guided support and personalized wellbeing insights.

Solo project by Ibraheem chand · 1 likes · 0 comments

Archive position — measured, not model output

1 like on Devpost

506 of the 7,856 archived projects have more likes, and 1,758 share exactly 1 — so this project's #1,055 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

What the company appears to be

FemAI is a self-reported privacy-first menstrual wellness app that enables users to track cycles, symptoms, mood, and energy while offering AI-guided support and personalized insights. It is described as a full-stack demo built for a hackathon.

What changed

The project was submitted as a hackathon entry (OpenAI 2026) and has no evidence of prior development or commercial traction beyond the author’s own account.

Single most important open question

Is there any evidence that FemAI has users, revenue, or adoption beyond its self-reported demo?

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What The Product Actually Is

The description states:

  • FemAI is a menstrual wellness app.
  • It allows users to register securely, track cycles, log symptoms and moods, complete daily check-ins, view summaries, chat with an AI wellness coach, manage privacy settings, and export or delete their data.
  • It includes partner-sharing foundations, notifications, admin insights, and a Sepolia testnet Premium payment flow.

Inference The app is described as a full-stack demo built for a hackathon, using React/Vite frontend, NestJS/TypeScript backend, PostgreSQL with Prisma, Redis, JWT authentication, and OpenAI-compatible AI integration. It also includes blockchain payment infrastructure (Ethereum Sepolia testnet).

Not evidenced No evidence of actual user base, live deployment, or production functionality beyond the demo.

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Positioning & Claim Evolution

The description states:

  • FemAI is a privacy-first menstrual wellness app.
  • It helps users track cycles, symptoms, and mood while providing safe AI-guided support and personalized wellbeing insights.
  • The app aims to be a calm, privacy-conscious space for understanding cycle patterns.

Inference FemAI positions itself as a health-focused, privacy-centric tool with AI integration for menstrual wellness.

Not evidenced No evidence of how this positioning evolved from earlier versions or whether it has shifted since the hackathon submission. No claims about market traction, user feedback, or competitive differentiation are provided.

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Target Customer & ICP

The description states:

  • FemAI is aimed at users who track menstrual cycles and wellness.
  • It supports privacy-conscious individuals seeking AI-guided support and personalized insights.

Inference The target customer appears to be women or people with menstrual cycles, particularly those interested in tracking their health and using AI for guidance.

Not evidenced No evidence of specific user personas, segmentation, or ICP validation. No data on how many users exist or what their needs are beyond the author’s self-report.

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Business Model & Pricing Evidence

The description states:

  • FemAI includes a Sepolia testnet Premium payment flow.
  • It supports browser-wallet integration for payments.

Inference There is an implied premium tier with blockchain-based payment infrastructure, but no pricing details or monetization strategy are provided.

Not evidenced No evidence of actual pricing, revenue model, or monetization beyond a testnet payment system.

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Technical & Delivery Signals

The description states:

  • Built with React and Vite (frontend), NestJS and TypeScript (backend), PostgreSQL with Prisma, Redis, JWT authentication.
  • Uses OpenAI-compatible AI integration.
  • Payment uses Ethereum Sepolia verification with browser-wallet support.
  • The app runs locally with PostgreSQL, Redis, frontend, and backend connected.

Inference The technical stack is modern and includes full-stack capabilities, AI integration, and blockchain payment infrastructure.

Not evidenced No evidence of production deployment, scalability, or live service delivery beyond a local demo.

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Traction & Maturity Signals

The description states:

  • FemAI was built as a hackathon project (OpenAI 2026).
  • It includes a working full-stack demo with authentication, database persistence, AI chat, cycle tracking, privacy controls, and blockchain payment foundations.
  • The team is small (1 member).

Inference The product is at an early stage, likely a prototype or demo, with no evidence of user adoption or commercial traction.

Not evidenced No evidence of users, revenue, customer acquisition, or product-market fit beyond the author’s own account.

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Competitive Context

The description states:

  • FemAI aims to be a calm, privacy-conscious space for menstrual wellness.
  • It integrates AI-guided support and personalized insights.

Inference It competes in the menstrual health and wellness app space, potentially with apps that offer cycle tracking, symptom logging, and AI support.

Not evidenced No evidence of competitive analysis, market positioning, or differentiation from existing players.

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Key Risks & Red Flags

  • The product is described as a hackathon demo with no evidence of traction or commercial viability.
  • It includes blockchain payment infrastructure (Sepolia testnet) but lacks real-world payment processing or user adoption.
  • The team size is 1, suggesting limited development capacity.
  • AI integration in health-related products raises safety and regulatory concerns, which are not addressed in the description.
  • No evidence of user feedback, product-market fit, or monetization strategy.

Inference The project is at a very early stage with no commercial evidence. Risks include lack of scalability, limited team, and unproven market demand.

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Diligence Questions To Ask The Founders

  1. What is the current user base or engagement level beyond the demo?
  2. How does FemAI ensure safety and compliance in AI-guided health support?
  3. Is there a plan to move from testnet to mainnet, and what are the timelines?
  4. What is the intended monetization strategy beyond the premium tier?
  5. Are there any partnerships or collaborations in place for distribution or validation?

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Investment/Partnership Verdict

Not evidenced.

The project is described as a hackathon demo with no evidence of traction, revenue, or user adoption. The description does not provide sufficient commercial signals to assess investment or partnership viability.

Confidence Low. This analysis is based entirely on self-reported information and lacks any independent verification or data on users, customers, or commercial performance.

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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.