OpenAI 2026 hackathon

LLNA PRO – Low-Latency Mobile Audio Framework for Unity

A Unity Asset Store package that brings native low-latency audio to Android and iOS, with a real-time synth, sampler, sequencer, native playback, and WAV export for mobile music apps.

Solo project by Barış Biltekin · 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 #5,042 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

LLNA PRO – Low-Latency Mobile Audio Framework for Unity is a self-reported Unity asset that aims to improve mobile audio performance for rhythm games, virtual instruments, and music production apps by integrating native Android and iOS audio systems. The author, Barış Biltekin, describes it as a cross-platform audio toolkit built with C#, Unity, and native audio technologies such as Oboe, AAudio, AudioUnit, and RemoteIO.

The framework includes components like a synthesizer, sampler, sequencer, offline renderer, WAV export, and timeline. It is positioned to help developers avoid Unity’s standard audio pipeline for low-latency applications on mobile platforms.

What Changed

The project evolved from solving a single audio latency issue into a full toolkit with multiple audio capabilities. It was submitted to the OpenAI 2026 hackathon.

Single Most Important Open Question

Is there evidence of developer adoption or usage beyond the author’s own development context?

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What The Product Actually Is

The description states that LLNA PRO is a Unity Asset Store package that brings native low-latency audio to Android and iOS. It includes:

  • Native playback for Android and iOS
  • A playable synthesizer, sampler, sequencer, audio timeline
  • Offline audio rendering and WAV export
  • Integration with Unity through C# components

It was built using Unity, C#, Oboe, AAudio, AudioUnit, RemoteIO, and supported by Codex for architecture and debugging.

Inference The framework is described as a toolkit that allows developers to build audio-based mobile apps without needing to implement native audio engines from scratch. It targets Unity developers working on rhythm games or music apps.

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Positioning & Claim Evolution

The author states that LLNA PRO was initially built to solve a single audio latency problem (around 150 ms) in rhythm games and virtual instruments. Over time, it evolved into a complete cross-platform audio toolkit.

It is positioned as a solution for developers who want to avoid Unity’s standard audio pipeline and instead use native audio systems for better performance on mobile platforms.

Claim

The framework makes complex native audio technology accessible through Unity components.

Inference It is not a standalone app but a developer tool or asset, likely intended for sale or distribution in the Unity Asset Store.

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Target Customer & ICP

The description states that the author develops mobile rhythm games, audio-based games, and music production apps with Unity. The framework is intended for developers working on:

  • Rhythm games
  • Virtual instruments
  • Drum machines
  • Music production apps

It is described as a mobile-first solution.

Inference The ICP (Ideal Customer Profile) likely includes indie or professional Unity developers building audio-intensive mobile applications, particularly those in the music or gaming space.

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Business Model & Pricing Evidence

The description does not provide evidence of pricing, monetization, or distribution strategy. It only states that LLNA PRO is a Unity Asset Store package, implying it may be sold through that platform.

Not evidenced No information on revenue model, pricing tiers, or whether it’s free, paid, or open-source.

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Technical & Delivery Signals

The framework is built with:

  • Unity
  • C#
  • Native Android audio (Oboe, AAudio)
  • iOS audio (AudioUnit, RemoteIO)
  • Codex for architecture and debugging

It supports:

  • Touch input responsiveness
  • Glissando keyboard interaction
  • Preset reusability
  • Native playback
  • Rendered audio output

Inference The framework is designed to be cross-platform, integrating with both Android and iOS native audio systems, and is intended to be easily integrated into Unity projects.

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Traction & Maturity Signals

The project was submitted to the OpenAI 2026 hackathon, suggesting it’s a prototype or early-stage product. There is no evidence of:

  • Revenue
  • Customers
  • User adoption
  • Product usage beyond the author's own development context

Not evidenced No data on downloads, user feedback, or market traction.

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Competitive Context

The description does not mention competitors or similar tools in the market. It implies that Unity’s standard audio pipeline is suboptimal for low-latency use cases, but no comparison to existing solutions is made.

Inference The framework likely competes with other Unity-based audio tools or native audio implementations, but there is no evidence of direct competition or market positioning.

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Key Risks & Red Flags

  • No revenue or customer data: The project appears to be a prototype or personal tool without commercial traction.
  • Single developer team: Only one member (Barış Biltekin) is listed, which may limit scalability or long-term maintenance.
  • Unverified claims: All statements are self-reported and unverified.
  • Hackathon submission: Suggests early-stage development with limited testing or market validation.

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Diligence Questions To Ask The Founders

  1. What is the current stage of development, and how far along is it from a production-ready product?
  2. Are there any existing users or developers using LLNA PRO in commercial projects?
  3. How does the framework compare to Unity’s built-in audio system in terms of performance and ease of use?
  4. Is the framework available for purchase or distribution through Unity Asset Store, and what is the pricing model?
  5. What are the specific technical limitations or compatibility issues with different mobile devices or OS versions?

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Investment/Partnership Verdict

Not evidenced: No data on revenue, customer base, or market traction to assess investment or partnership viability.

Inference The project appears to be a developer tool in early development, likely targeting indie developers or small teams. It has not yet demonstrated commercial adoption or scalability.

Given the self-reported nature of the description and lack of evidence for traction or monetization, this is a highly speculative opportunity with limited due-diligence support at this stage.

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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.