Perilune

The company appears to be a solo developer project named Perilune, an interactive browser-based orbital engineering game built with Next.js, Three.js, Supabase, and OpenAI tools. The author states it simulates realistic spaceflight mechanics in a scaled Sun–Earth–Moon system, allowing players to design spacecraft, launch missions, and experience mission planning through guided scenarios.

What changed: The project evolved from a personal interest in spaceflight and orbital mechanics into a playable prototype with multiple modes (Sandbox, Exploration, Space Program), a guided Artemis IV scenario, and an AI flight director (Pip). It was submitted to the OpenAI 2026 hackathon.

The single most important open question: Is there any evidence of commercial traction, user adoption, or monetization strategy beyond the author’s own development efforts?

Analysis basis: Self-reported only. No revenue, customer data, or independent verification provided. All claims are from the project description and author's own submission.

• The description states Perilune is a browser-based orbital engineering game.
• It simulates a physically scaled Sun–Earth–Moon system.
• Players can:
  • Design rockets in a Workshop.
  • Launch from Earth, reach orbit, create maneuver nodes, transfer to the Moon.
  • Rendezvous and dock with other spacecraft.
  • Land on moons and return home.
• It includes guided scenarios, such as:
  • First Light (launch and orbital flight).
  • Second Light (lunar transfers).
  • Artemis IV preview (representative lunar mission involving Orion operations, descent, landing, ascent, redocking, atmospheric entry, splashdown).
• There is an optional AI flight director named Pip, powered by GPT-5.6.
• The game supports:
  • Multiple active vessels.
  • Alarms.
  • Communications relays.
  • Atmospheric entry prediction.
  • Transfer planning.

Inference: The product is a simulation-based educational or entertainment tool, not a commercial SaaS offering.

• The author states the goal was to make orbital mechanics interactive, allowing anyone to “design a spacecraft, fly a mission, learn from failure, and experience what it is like to think like a flight director.”
• It positions itself as an alternative to specialized professional mission-planning software that is hard for newcomers to access.
• The project evolved from a personal interest in spaceflight into a playable prototype with progression, including:
  • A guided scenario structure.
  • An AI flight director (Pip).
  • Multiple play modes: Sandbox, Exploration, Space Program.

Claim vs. Fact: The author claims the game is educational and interactive, but no evidence of user feedback, adoption metrics, or usage data is provided.

• The description states that Perilune is intended for:
  • Anyone interested in spaceflight.
  • Those who want to learn orbital mechanics through simulation.
  • Users who want to experience mission planning like a flight director.
• It includes guided scenarios, suggesting it targets beginners or learners.
• The inclusion of multiple play modes (Sandbox, Exploration, Space Program) implies a range of user skill levels.

Inference: The ICP is likely space enthusiasts, students, or hobbyists interested in orbital mechanics. No evidence of specific customer segments or personas.

• No pricing information, monetization strategy, or business model is stated.
• The project is described as a personal development effort by one developer.
• It includes no mention of:
  • Subscription plans.
  • Freemium tiers.
  • In-app purchases.
  • Licensing or enterprise offerings.

Not evidenced: No evidence of any commercial structure, pricing, or revenue model.

• Built with:
  • Next.js, Three.js, Supabase, OpenAI (GPT-5.6).
  • TypeScript for backend and rendering.
• Uses analytical orbital mechanics to maintain celestial body positions under time warp.
• Implements double precision for simulation, converting to f32 for GPU rendering.
• Assets are generated using NASA and NOAA datasets.
• Includes:
  • Vitest for core simulation testing.
  • Playwright for browser flight path testing.
  • Supabase for cloud saves and auditing.
  • AI tools (Codex, GPT-5.6) used in development, debugging, and review.

Inference: The project shows technical sophistication, especially in simulation precision and rendering. However, no evidence of production deployment or delivery to users beyond the author’s own use.

• The project is described as a playable prototype.
• Includes:
  • A progression slice (workshop → launch → orbit → transfer → landing → recovery).
  • A guided Artemis IV scenario with 11 chapters.
  • Multi-vessel control, docking, and atmospheric entry.
• The author notes that the Artemis IV preview is representative, not accurate to NASA’s final flight plan.
• It was submitted to a hackathon (OpenAI 2026).

Not evidenced: No evidence of user engagement, retention, or adoption. No data on active users, usage frequency, or community growth.

• The description does not mention direct competitors.
• It is positioned as an alternative to specialized mission-planning software that is hard for newcomers to access.
• It may compete with:
  • Educational games or simulators focused on orbital mechanics.
  • Spaceflight simulation tools (e.g., KSP, Orbiter).
  • AI-powered flight planning tools.

Not evidenced: No competitive landscape analysis, no mention of existing tools or market positioning.

• The project is a single-person effort with no team or external support.
• It is described as a personal development project, not a commercial product.
• No evidence of:
  • Revenue.
  • Customers.
  • Product-market fit.
  • Scalable delivery mechanisms.
• The use of GPT-5.6 and AI tools raises questions about dependency on external services, which may not be sustainable or scalable.
• The project is in development, with no indication of a release or commercialization plan.

Inference: High risk of lack of traction, scalability, or commercial viability without further development or team expansion.

1. What is the intended path to monetization or commercialization?
2. Are there any users or early adopters beyond the developer?
3. How is the AI flight director (Pip) integrated into gameplay, and what are its limitations?
4. Is there a plan for ongoing updates or expansion of the solar system?
5. What are the technical dependencies on external services like OpenAI or Supabase?
6. How does the project intend to scale beyond a single developer?