Zibra AI

What it does

GPU-native data orchestration platform for physical and spatial AI. Spatial AI isn't compute-bound — it's data-bound. Massive volumetric datasets create a data gravity problem: I/O bottlenecks starve GPUs and stall training despite huge compute investment. Zibra removes that bottleneck — over 97% in size reduction, 600+ GB/s decompression, delivered in the compressed unified format directly into GPU. 40% better GPU utilization. 30% faster model convergence. This is the missing data layer.

ZibraXYZ compresses, streams, and serves volumetric simulation data directly to GPUs. 30× compression. 500 GB/s throughput. Talk to our R&D team.

Compressing, streaming, and serving volumetric data directly to your GPUs. Eliminate I/O bottlenecks. Increase GPU utilization. Train physics models faster. Physics simulations generate massive, complex datasets — and every stage of your pipeline pays the tax. Retaining full-resolution datasets across runs is unsustainable. Teams downsample or discard data. Data transfer between storage and GPU is the limiter. GPUs sit idle waiting for data. VTK, HDF5, OpenVDB, custom formats — each needs its own pipeline and maintenance. Sharing multi-TB datasets across teams means days of transfers and duplicated infra. Designed for teams running large-scale physics simulations across domains. Whether…from zibra.ai

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