TRL 7 — Operational Verification

Command the Physics.

High-precision differentiable physics engines for pharmaceuticals, energy, and advanced computing. 10⁻¹⁴ precision. Zero-trust security. Real-time deployment.

The Simulation Bottleneck

Legacy solvers take days.
We take milliseconds.

Traditional CFD and FEA simulations are computationally prohibitive for real-time industrial optimization. Quantum Bridge AI replaces multi-day render times with Neural Surrogates that maintain machine-precision fidelity.

100–1000×

Speedup over legacy FEM solvers

10⁻¹⁴

Precision floor (machine epsilon)

10⁻⁷

Encrypted inference fidelity

Core Technology

Three engines. One mission.

Every component is built for mathematical certainty, not probabilistic approximation.

Veritas-JAX

Differentiable Physics Engine

KenCarp4 IMEX solvers + SIREN neural layers resolve stiff reaction-diffusion dynamics at 10⁻¹⁴ precision. End-to-end JAX/XLA differentiability enables exact gradient-based optimal control.

Laminar-GND

Continuous Graph Neural Diffusion

O(1) memory via the Adjoint Sensitivity Method. Replaces O(N²) Vision Transformers with continuous reaction-diffusion physics on sparse graph topologies — scaling to billion-node networks.

Zero-Trust Vault

Homomorphic Encryption (TenSEAL)

Compute on encrypted industrial telemetry without exposing proprietary process parameters. CKKS-encrypted inference with < 10⁻⁶ plaintext-ciphertext divergence.

TRL 7 Verified
Background IP — KTH Innovation Legal
JAX / XLA Native

Let's solve the equations that define your reality.

Ready to transition your R&D pipeline from legacy solvers to real-time Neural Surrogates with machine-precision fidelity?

Start the Conversation