OpenAI 2026 hackathon

Swimphony

A goldfish's movement becomes generative music, ambient light, and a projected trail.

Solo project by Tadahiro Kawamura · 0 likes · 0 comments

View the project on Devpost

Archive position — measured, not model output

0 likes on Devpost

2,263 of the 7,850 archived projects have more likes, and 5,587 share exactly 0 — so this project's #7,077 place in the like-ranked listing is a tie-break inside that group, not a ranking.

Projects (log scale)

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1k
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05,587
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3–4132
5–975
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Likes on Devpost. ▲ marks this project's group.

Show the figures
LikesProjectsShare of archive
05,58771.2%
11,75822.4%
22843.6%
3–41321.7%
5–9751.0%
10+140.2%
Devpost like counts for all 7,850 archived projects, captured when this archive was built.

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Executive Summary

What the company appears to be

Swimphony is a self-reported one-person project that turns goldfish movement into generative music, ambient light, and visual projection using a single camera and AI. The author states it was built for an OpenAI hackathon and includes no evidence of revenue, customers, or commercial traction.

What changed

The project is presented as a prototype or proof-of-concept, not a product in development. It has no stated evolution from prior versions, nor any indication of ongoing work beyond the submission.

Single most important open question

Is there any evidence that Swimphony has moved beyond the author's own development and into user testing, deployment, or monetization?

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What The Product Actually Is

The description states that Swimphony is a one-camera web app that tracks one goldfish and translates its movement into:

  • Generative music (via Tone.js)
  • Ambient light (via Philips Hue API)
  • A projected visual trail (via a projector)

It uses:

  • Next.js, React, TypeScript
  • HTML Canvas for tracking
  • GPT-5.6 as an AI conductor
  • Zod for schema validation
  • Tone.js for sound generation

The system includes:

  • Calibration to extract position, speed, direction, acceleration, apparent size, and confidence from the fish’s movement.
  • A deterministic telemetry mode that allows performance without a camera or fish.

Inference The app is a browser-based interactive experience, not a commercial product. It runs in a web browser with no stated backend infrastructure beyond local Codex sessions.

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Positioning & Claim Evolution

The author states Swimphony was built to:

  • Make an aquarium feel less like something we watch and more like something we can listen to.
  • Treat goldfish movement as a performance without altering the fish’s behavior.

It is described as a “one-camera web app” that uses AI to generate structured sound-and-light presets based on user mood input (e.g., “quiet midnight aquarium”). It also includes:

  • A fallback system for when tracking fails.
  • A deterministic mode for judges or testing without hardware.

Inference The positioning is experimental, artistic, and exploratory. There is no claim of scalability, commercial viability, or market readiness.

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Target Customer & ICP

The description does not state a target customer or ideal customer profile (ICP). It only describes the author’s intent to explore how aquariums could be experienced differently.

Inference The project appears aimed at:

  • Hackathon participants
  • Artistic or experimental users
  • Developers interested in real-time interaction and AI integration

No evidence of a defined market segment, user persona, or commercial customer base.

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Business Model & Pricing Evidence

There is no evidence of a business model or pricing structure. The project is described as a hackathon submission with no mention of monetization, licensing, or sales channels.

Inference No business model is evident beyond the author’s own development and demonstration.

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Technical & Delivery Signals

The system uses:

  • Next.js, React, TypeScript
  • HTML Canvas for tracking
  • Tone.js for sound generation
  • GPT-5.6 as a server-side conductor
  • Zod for validation
  • Philips Hue API for lighting control
  • A projector view for visual output

Key technical features include:

  • Camera input (live or sample video)
  • FishState model to decouple tracking from performance engine
  • Confidence-aware fallback behavior
  • Server-side GPT-5.6 session with schema-constrained outputs
  • Deterministic telemetry mode for testing without hardware

Inference The app is a browser-based prototype with clear separation of concerns and safety mechanisms, but no evidence of production deployment or scalability.

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Traction & Maturity Signals

The project is described as a hackathon submission, not a product in use. It includes:

  • Automated tests, linting, and build processes
  • A production build that passes
  • A documented development process with Codex collaboration

Inference The project shows maturity in prototype form but lacks evidence of user adoption, customer feedback, or market traction.

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Competitive Context

There is no mention of competitors or market context. The description does not reference similar products, platforms, or use cases in the broader SaaS, developer tooling, or marketplace space.

Inference No competitive landscape is evident beyond the author’s own project scope and intent.

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Open Questions & Risks

  • No commercial traction: The project is a hackathon submission with no evidence of users, revenue, or adoption.
  • Unproven scalability: The system is described as a browser-based prototype, not a scalable product.
  • Limited market relevance: No stated target customer or use case beyond artistic exploration.
  • Self-reported only: All claims are unverified and based on the author’s own description.

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Questions the description leaves open

  1. What is the intended user base for Swimphony beyond the hackathon?
  2. Has the system been tested in real-world aquariums or installations?
  3. Are there plans to commercialize or scale this project?
  4. How does the AI conductor (GPT-5.6) integrate with other systems or APIs?
  5. What are the technical limitations of the current prototype that would need to be addressed for production use?

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Overall Assessment

Not evidenced.

There is no evidence of a business model, revenue, customers, or commercial traction. The project is described as a hackathon submission with no indication of ongoing development, user testing, or monetization.

Confidence: Low.

This is a self-reported prototype with no external validation or market signals. Any potential for investment or partnership depends on future development and evidence of traction, which is not present in the description.

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Source

Submitted to the OpenAI 2026 hackathon on Devpost. Project home on Devpost. Back to the full gallery on Devpost.

This competitive analysis was produced by top-founders.com (opens in a new tab)

Generated by a language model from this project's public Devpost page — its tagline, the author's own write-up and any built-with tags listed there — as captured in August 2026. Short quotations are the author's words. It is an opinion on the idea as a business, not on the people behind it, and it reflects the description as published then. If the project has moved on, request a correction below. The analysis is not independent research and contains no verified traction, revenue or customer data.

An independent guide by KFG International LLC — not affiliated with, endorsed by, or connected to Devpost or OpenAI.

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