GDBS (Geometric Database System) is a browser-native verifiable-computation platform. One deterministic engine runs computation across many domains - physics checked against published references, legal and compliance figures computed against the controlling statute, forensic and financial math - and reports how much to trust every result instead of asking you to assume, with each answer traceable to the source it came from. For scientific work it is also where you validate a method before taking it to HPC; for most other domains there is no cluster at all, and GDBS is the whole tool.

For scientific work, it is not a replacement for the cluster - it is the step before it. HPC codes (VMEC, VASP, LAMMPS, Gaussian) run production-scale problems that need a mesh, an allocation, and a job queue. GDBS lets you develop and validate the same method first at browser and single-GPU scale: no allocation grant, no job scheduler, no specialized infrastructure, and a trust verdict on every result so you know the setup is right before you scale it. You iterate in seconds here, then take the validated method to HPC for the full run. For most other domains GDBS serves - legal, compliance, finance, forensic - there is no cluster at all, and GDBS is the whole tool.

No. GDBS is deterministic analytic geometry. There is no training data, no loss function, no gradient descent, no stochastic sampling, and no convergence criteria. The same inputs always produce the same outputs on every machine. It is not an approximation or a neural surrogate - it is an alternative computational representation of established physics.

GeoNum (Geometric Number Scale) is the precision arithmetic system underlying all GDBS computations. Standard IEEE 754 floating-point does not report how much precision a result has left. On a Hawking radiation calculation whose operands span 64 orders of magnitude (ℏ ≈ 10⁻³⁴ to M_⊙ ≈ 10³⁰), GeoNum and IEEE 754 agree on the value; what GeoNum adds is a drift figure of zero, telling you the agreement is real rather than luck. Where IEEE 754 does fail outright, such as 171 factorial overflowing to Infinity or Muller's recurrence converging confidently to 100 when the true limit is 6, GeoNum either continues in log space or flags the result as unreliable before you act on it.

GeoNum shifts the precision challenge from bit-width to geometric structure. Four mechanisms work together:

• Zone-tessellated addressing - values are encoded as field intensities within a geometric structure where zones identify the logarithmic scale region and shades provide discrete tessellation, maintaining consistent representation regardless of dimensionality d or node count n.
• Logarithmic space arithmetic - by operating natively in logarithmic space, the system reconstructs precise values from zone and intensity rather than quantized bits. As n spans extreme dynamic ranges, drift accumulates only from the final quantization step - not from compounding intermediate rounding errors.
• Domain-configurable zone boundaries - O(n^1/d) scaling is handled by tuning zone boundary functions to match each domain's characteristic grid (uniform for CFD, spherical-harmonic-aligned for geophysics, lattice-symmetric for materials). Each axis of the d-dimensional precision grid carries n^1/d resolution steps, achieving uniform precision density without exponential storage cost.
• Transparent drift tracking - a drift compartment captures the fractional remainder of every arithmetic operation, so you can monitor exactly how much precision is retained as node resolution increases.

Hardware agnosticism: compute-intensive kernels are dispatched to WebGPU as a raw parallel substrate - but precision is not a hardware property. Whether the GPU is an integrated laptop chip, a mobile device, or a high-end workstation, the zone-tessellated structure and drift compartment produce the same value and the same reported drift. A researcher on a phone sees the same result, and the same statement of how much of it survived the arithmetic, as someone on a desktop. Precision lives in the geometry, not in the silicon.

Every physical system maps its parameters to coordinates in 13-dimensional position space, decomposed into four coherence tiers: Core (7D - fundamental observables), Magnitude (9D - energy scales), Phase (11D - oscillatory structure), and Proportion (13D - ratio relationships). Recursive relational layers up to 31D evaluate cross-tier coherence. Several physical outputs - β_crit, bulk modulus, gate fidelity, CMB multipole peaks - are read from the geometry of these coordinate relationships as a compact reduced-order representation. Where a problem genuinely needs a full PDE or SCF solve (DFT, numerical relativity, CFD), GDBS runs that solver too and reports its convergence and trust verdict.

Yes. The engine ships with re-runnable test suites that gate every release, and results are compared against a published reference where one exists. Representative results:

• GW150914 final black-hole mass: 63.02 M_☉ against 63.1 (Abbott et al., LIGO/Virgo), 0.13%; final spin 0.6855 against 0.69, 0.65%
• GW170817 chirp mass: 1.185 M_☉ against 1.188 (Abbott et al.), 0.3%
• Quantum chemistry (H₂, H₂O, CH₄): Hartree-Fock energies within 0.5 to 2% of the STO-3G reference (Szabo and Ostlund)
• Blasius flat-plate wall shear: 0.4696 against the canonical 0.4696, within 0.002 (Falkner and Skan, 1931)
• Numerical-relativity constraint convergence against the analytic zero: Hamiltonian order 3.86, momentum order 3.92 (AwA gauge-wave initial data under harmonic slicing; the AwA testbed protocol is not run). Factor-2 self-convergence reads 3.946, reported as a consistency check rather than as validation
• GPU constrained transport: magnetized accretion torus held |div B| to 2.37e-4 over the run, every observable carrying a trust verdict

Many domains, in two layers. The validated science layer spans seven physics areas, each with dedicated scan types and benchmarks against published references: Plasma & Fusion (tokamak/stellarator stability, MHD, FRC), Materials Science (elastic moduli, band gaps, phase transitions), Cosmology (galaxy rotation, CMB, dark matter), Geophysics (seismology, gravity anomalies, tectonic stress), Fluid Dynamics (boundary layers, drag, compressible flow), Quantum Information (error correction, qubit fidelity, entanglement), and Medical/Molecular (drug screening, protein stability, nanoparticle uptake). The professional layer adds deterministic, statute-cited tools for legal practice, regulatory and CMMC compliance, tax and forensic accounting, insurance claims, real-estate closings, HR and benefits, and RF metrology. Same engine, same trust verdict, every result traceable to its source.

GeoNum is not peer-reviewed. Precision results are validated against published HPC reference values and are fully reproducible by any user of the platform.

Yes. Results are deterministic and reproducible. Research users are required to cite GDBS in all published work, presentations, and reports. The GeoNum precision system is separately. When citing GDBS itself, use:

"Computational analysis performed using GDBS (Geometric Database System), developed by VaultSync Solutions Inc. https://gdbs.getvaultsync.com"

All physics computations run as WebAssembly in your browser - no server round-trips, no data sent unless you choose to save it. Results are only stored on GDBS servers if you explicitly use the Save Run feature. The platform includes a GQL query engine, database browser, CSV export, and a REST API for scripted workflows. If you don't save it, we don't keep it.