Greneta Optimizer 2.0

The metaverse and digital twin era has arrived, but ultra-large 3D data files are becoming a bottleneck. Precise 3D scans of factory equipment or medical 3D images can range from hundreds of MB to several GB, making real-time transmission and rendering difficult with current networks and devices.

Previously, file sizes were reduced by lowering quality or enduring long loading times, which reduced on-site usability. For example, transmitting hundreds of MB of 3D MRI data for urgent remote medical diagnosis causes delays, and even when wanting to use high-quality 3D models for AR/VR training, device performance limitations require reducing them to lower detail.

Furthermore, existing compression tools often damage the details of 3D models (the "MP3-ification of 3D" problem), making them undesirable for field professionals. In other words, the weight of 3D data is an obstacle to the spread of spatial computing.

Greneta Optimizer 2.0 achieves both outstanding compression rates and quality preservation. Through an AI quantization algorithm, it compresses models of several GB to the MB level within seconds while maintaining geometric precision, achieving up to a 99.6% reduction in size. This is a significantly higher figure compared to competing solutions, surpassing the 50-90% compression commonly used in the industry.

At the same time, it completely preserves visual fidelity, ensuring no visible difference before and after compression. In terms of ease of use, it provides a one-click preset interface and modular API integration, making it easy for non-experts to use and seamlessly integrates into enterprise workflows.

In particular, it also provides the added value of AI filling in holes or errors in 3D scan models with an automatic mesh restoration function. Support for major platform plugins such as Unreal, Unity, and NVIDIA Omniverse also sets it apart. In summary, it is a next-generation 3D optimization engine that solves the quality degradation issues of existing compression tools and has speed, convenience, and scalability.

The main customers are industrial areas that handle large-capacity 3D data, such as manufacturing, construction, medical, and content. For example, automobile or aviation manufacturers can use it to lighten CAD drawings (digital twins) for collaboration, or construction companies can use it to share building 3D scans to the cloud.

Medical IT companies that need to remotely transmit medical image (CT/MRI) originals can also adopt it, and game/movie VFX studios can adopt it to quickly process ultra-high-resolution 3D assets. In addition, AR/VR content creators can optimize models with this technology to implement high quality even on mobile devices.

As B2B software, it will be sold to companies in the form of solutions (libraries or cloud APIs) for their existing 3D pipelines. Customized applications are also expected through collaboration with large companies in each industry.

As a software-based solution, it is easy to enter the global software market. It has already joined the NVIDIA Inception program to seek global partnerships and is also working to discover overseas customers through CES participation.

The technology itself has no specific environmental constraints, but there is a challenge in continuously expanding 3D data standards or file format compatibility. Solving this can create demand in all regions where XR/metaverse is growing.

Furthermore, since it is an AI compression technology, it is also possible to expand applications to other data type compression fields such as video/image. Currently, it starts by targeting niche markets by industry as an innovative professional tool, but it can grow into a wide market in the future where digital twin infrastructure becomes essential.

There are no special restrictions in terms of regulations, but when applied to fields such as medicine, reliability verification of data accuracy will be required.

It won the CES Innovation Award with favorable reviews as "the key to solving data bottlenecks in the industrial metaverse." The judges highly praised the accurate identification of realistic problems in 3D data processing and the presentation of solutions, and expressed surprise at the performance figures (99% compression). Market experts also expressed anticipation, saying that it is a technology that removes factors hindering the popularization of AR/VR.

However, some have mentioned that this technology may be a solution that is too far ahead. In other words, the variable is how quickly demand will be created at a stage where many companies are not actively using 3D data. In addition, the possibility that large companies such as NVIDIA or Autodesk may develop similar technologies in-house is also cited as a competitive risk.

Nevertheless, the current performance of Greneta is mainly positively evaluated as *"space compression technology that has taken a step into the real world."* It is expected that it can change the market landscape if continuous technology leadership and actual field application cases emerge.