One deterministic engine covers many domains: physics checked against published references, legal and compliance figures computed against the controlling statute, and forensic and financial math. Every answer is traceable to the source it came from.

For scientific work it is 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.

HPC codes such as VMEC, VASP, LAMMPS and 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 specialised 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 the other domains GDBS serves, legal, compliance, finance and forensic, there is no cluster at all.

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, but an alternative computational representation of established physics.

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 fails outright, GeoNum either continues in log space or flags the result as unreliable before you act on it. Two cases: 171 factorial overflows to Infinity, and Muller's recurrence converges confidently to 100 when the true limit is 6.

Zone-tessellated addressing. Values encode as field intensities within a geometric structure, holding representation steady regardless of dimensionality d or node count n.

Logarithmic-space arithmetic. Values reconstruct from zone and intensity rather than quantized bits, so drift accumulates only at the final quantization step, not from compounding intermediate rounding.

Domain-configurable zone boundaries. Zone boundaries tune to each domain's characteristic grid, giving each axis of the d-dimensional grid n^1/d resolution steps without exponential storage cost.

Transparent drift tracking. A drift compartment captures the fractional remainder of every operation, so retained precision stays measurable as resolution increases.

Precision is not a hardware property. Compute-intensive kernels dispatch to WebGPU as a raw parallel substrate, but whether the GPU is an integrated laptop chip, a phone or a high-end workstation, the same value and the same reported drift come back.

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, including β_crit, bulk modulus, gate fidelity and CMB multipole peaks, are read from the geometry of these relationships as a compact reduced-order representation. Where a problem genuinely needs a full PDE or SCF solve, such as DFT, numerical relativity or CFD, GDBS runs that solver too and reports its convergence and trust verdict.

The engine ships with re-runnable test suites that gate every release, and results are compared against the published value rather than tuned to it.

Constraint-convergence orders use AwA gauge-wave initial data under harmonic slicing; the AwA testbed protocol itself is not run. Factor-2 self-convergence reads 3.946 and is reported as a consistency check, not validation, since self-convergence cannot detect converging to the wrong answer.

Plasma and fusion (tokamak and 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 and 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.

GeoNum has not been through peer review. What stands behind it is the published-reference comparison and the fact that any user can re-run it.

Cite GDBS in all published work, presentations and reports:

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

There are no server round-trips and no data sent unless you choose to save it. Results are stored on GDBS servers only if you explicitly use the Save Run feature.

The platform includes a GQL query engine, a database browser, CSV export, and a REST API for scripted workflows.