QTT-Native Computational Substrate
HolonomiX does not build applications on top of existing databases. It replaces the data representation layer entirely. Quantized Tensor Train decomposition stores the structural form that generates your data, then executes directly on that form in GPU VRAM.
Three components. One execution model.
QTT Substrate
Data enters once and is decomposed into quantized tensor train form. 200 TB of raw data becomes 1.3 TB. Lossless. Audited across all 109 / 109 operations.
HyperTensor-VM
HyperTensor-VM is a 2.2M SLOC GPU runtime executing directly on NVIDIA hardware. Custom Triton kernels, cuBLAS GEMM, and cuSOLVER serve all query patterns from compressed form in VRAM.
Governance
The Oracle Governor classifies structural form on arrival. The Canonical Data Atlas (894 entries, 92 rules) informs verdict classes. The Rank Governor constrains precision and keeps execution bounded.
Data arrives messy. The substrate makes it executable.
HX-SDP exists because the substrate changes what is computable.
HX-SDP is powered by a fundamentally new compute substrate: Quantized Tensor Train decomposition executed by a custom GPU runtime. The substrate is the moat. It changes the unit economics of data representation, making previously uncomputable workloads computable and previously expensive workloads economical.