OpenAI 2026 hackathon

OpenDigitalTwin

A lightweight web-based digital twin for robot simulation, OPC UA integration, and industrial automation.

Solo project by Yunsoo Jang · 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 #5,705 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

OpenDigitalTwin is a browser-based digital twin platform for industrial automation. The author describes it as a lightweight tool that allows small manufacturers and engineering teams to simulate robot motion, visualize automation data, and validate machine layouts using only a web browser.

What changed

The project was submitted to the OpenAI 2026 hackathon by a single developer (Yunsoo Jang). It is described as a prototype with functional OPC UA integration, 3D visualization, and robot kinematic simulation. The author states that it was built in a short timeframe using React, TypeScript, and Three.js.

The single most important open question

Is there any evidence of traction or commercial adoption beyond the hackathon submission?

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What The Product Actually Is

The description states that OpenDigitalTwin is a browser-based environment for building and testing industrial 3D scenes, designed to help small manufacturers validate machine layouts, robot motion, and PLC data connections without requiring expensive simulation tools.

It supports:

  • Importing robot and equipment geometry
  • Configuring robot links, joints, tools, TCPs, and coordinate frames
  • Positioning objects using X, Y, Z, Roll, Pitch, and Yaw
  • Creating robot poses and organizing them into executable Jobs
  • Visualizing robot and object motion in a 3D scene
  • Binding scene objects to OPC UA variables for live data visualization
  • Saving and reloading digital-twin projects
  • Performing geometry-based collision checks

The system uses a middleware gateway to connect to OPC UA servers, as browsers cannot directly communicate with native OPC UA endpoints.

It is built with:

  • React, TypeScript, Three.js, React Three Fiber, Zustand, Vite
  • Technologies such as Docker, GLB, STEP, HTML5, CSS3, WebSocket, and OPC UA

Inference The product appears to be a prototype tool for early-stage industrial validation, not a full-fledged engineering or simulation platform.

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Positioning & Claim Evolution

The author states that OpenDigitalTwin is not meant to replace advanced physics simulation or safety-certified tools, but instead offers an accessible starting point for small businesses.

It positions itself as:

  • A lightweight web-based alternative to Unity, Unreal Engine, or industrial physics platforms
  • A tool for early-stage kinematic validation
  • A way to visualize automation data and communicate machine concepts using only a browser

The author also notes that the project was initially more ambitious but narrowed its scope to focus on:

  • OPC UA-driven object motion
  • Browser-based robot kinematic verification

Claim

The tool aims to make industrial digital twin development faster, more accessible, and less resource-intensive for small manufacturers.

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Target Customer & ICP

The description states that the target audience includes:

  • Small manufacturers
  • Engineering teams
  • Users who need to verify machine layout, robot motion, or PLC data connection before committing to physical equipment

It is implied that these users are likely:

  • Not using full simulation tools due to cost or complexity
  • Looking for a way to validate early-stage designs without specialized expertise

The author also mentions that the tool is intended for those who cannot dedicate a large budget or specialized team to industrial simulation.

Inference The ICP appears to be small-to-medium-sized manufacturers and engineering teams working in industrial automation, with limited access to advanced tools.

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Business Model & Pricing Evidence

There is no evidence of pricing, business model, or monetization strategy in the description.

The project is described as a hackathon submission by a single developer (Yunsoo Jang), with no mention of any commercial offering or revenue streams.

Claim

The tool is presented as a prototype for early-stage validation and not yet positioned for sale or licensing.

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Technical & Delivery Signals

The system architecture includes:

  • A middleware OPC UA gateway
  • A browser-based runtime store
  • Integration with Three.js 3D rendering
  • Support for STEP, GLB, and other CAD formats
  • Use of React, TypeScript, Zustand, Vite

Key technical features include:

  • OPC UA variable binding to 3D objects
  • Clear indication of data ownership (manual vs. OPC UA)
  • Robot Jobs with configurable transition speeds
  • Geometry-based collision checks
  • Support for manual and OPC UA-controlled transforms

The system is described as having:

  • A production web build
  • 2,190 automated unit tests

Inference The tool is built with modern web technologies and has a clear separation between data ownership and visualization.

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Traction & Maturity Signals

There is no evidence of traction or adoption beyond the hackathon submission.

The project is described as:

  • A prototype
  • Built in a short timeframe (hackathon)
  • Submitted to the OpenAI 2026 hackathon
  • Not yet commercialized or deployed at scale

No customer data, revenue figures, usage metrics, or user feedback are provided.

Absence of evidence

No indication of:

  • Customers
  • Revenue
  • Product usage
  • Market traction
  • Commercial deployment

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Competitive Context

The author states that OpenDigitalTwin is not intended to replace advanced tools like Unity, Unreal Engine, or industrial physics platforms. However, it aims to offer a lightweight alternative for early-stage validation.

It competes with:

  • Industrial simulation tools
  • 3D visualization platforms
  • PLC integration environments

The author does not mention any direct competitors by name, nor does the description provide market positioning or competitive differentiation beyond its lightweight nature and browser-based delivery.

Inference It is positioned as a low-cost, early-stage validation tool, not a full simulation platform.

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Key Risks & Red Flags

  • No commercial traction or adoption: The project is described only as a hackathon submission.
  • Single developer team: No indication of a larger team or organizational support.
  • Prototype status: Not yet a production-ready product.
  • Limited scope: The author narrowed the demo to a specific workflow, not a full platform.
  • Dependency on middleware: Relies on OPC UA gateway for connectivity, which may be a limitation in some environments.
  • No pricing or monetization model: No evidence of how it would generate revenue.

Red flag

The lack of any commercial or user feedback makes it difficult to assess real-world utility or demand.

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Diligence Questions To Ask The Founders

  1. What is the current status of the product? Is it being used in any real-world applications?
  2. How does the middleware gateway architecture scale, and what are its limitations?
  3. Are there any plans for monetization or commercial deployment?
  4. Has the tool been tested with actual industrial users or partners?
  5. What are the main technical challenges that remain unresolved?
  6. How does the team plan to evolve from a prototype to a scalable product?

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Investment/Partnership Verdict

Not evidenced.

There is no evidence of:

  • Revenue
  • Customers
  • Product-market fit
  • Commercial traction
  • Team scalability or funding

The project is described as a hackathon submission by one developer, with no indication of commercial viability, market demand, or investment readiness.

Inference The tool may have potential as a proof-of-concept for early-stage industrial validation, but it is not yet ready for investment or partnership consideration. It would require further development, traction, and commercialization before being evaluated as a viable business opportunity.

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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.