The Physics Engine for Industrial Intelligence
Automated CAD-to-solve workflows. We replace empirical trial-and-error with mathematical certainty—delivering bitwise-deterministic CFD results in minutes, not days.
7.2 min
Solve Time
NVIDIA H100 · 9.2M Nodes vs. 3-Day Legacy CFD
$0.42
Compute Cost / Run
Full-fidelity solve, on-demand H100 pricing
1000×
Speedup
Over legacy FEM / CFD solvers
10⁻¹⁴
Solver Precision
Bitwise-deterministic KenCarp4
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
From CAD file to answer — no code required.
Three pillars turn a raw geometry file into a physically-grounded, interactive result in minutes.
Bring Your Own Boundary
No-Code CAD Ingestion
Drag-and-drop your .STL or .STEP geometry. The platform auto-generates a validated solver .json config — no meshing scripts, no manual boundary-condition wrangling.
Constrained MAS Orchestration
LLM-in-the-Loop, Zero Hallucinations
A multi-agent system autonomously parses CAD metadata and routes the case to the correct JAX solver, bound by strict schema contracts — the LLM handles the workflow, Axiom handles the math.
Millisecond Interactive Visualization
Sub-Second Thermal Feedback
Explore results the instant they compute. Thermal, flow, and stress fields render interactively in-browser — no round trip to a desktop CFD viewer.
Four engines. One mission.
Every component is built for mathematical certainty, not probabilistic approximation.
Axiom Engine
Differentiable Physics Engine
KenCarp4 IMEX solvers + SIREN neural layers resolve stiff reaction-diffusion dynamics at 10⁻¹⁴ precision. End-to-end continuous computational graph 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.
Multi-Agent System
Constrained MAS Orchestration
LLM agents handle data extraction and logistics routing, bound by strict Pydantic data contracts and human-in-the-loop gates. The AI handles the workflow; Axiom handles the math — zero hallucinations in critical decisions.
A visual workflow platform, backed by real math.
No-code by default. Fully programmable when you need it.
1. Ingest
Drop a .STL / .STEP file. Config auto-generated.
2. Orchestrate
MAS agents route the case to the correct JAX solver.
3. Solve & Render
H100-accelerated solve, visualized in-browser in ms.
Bridge to Quantum Infrastructure
Quantum Bridge AI is built on continuous, differentiable physics — the same substrate quantum computing runs on. That makes our platform a forward-compatible on-ramp to the QC era, not a classical dead end.
European Quantum Ecosystem & Deployment
Quantum Bridge AI does not build in a vacuum. We actively align with the European deep-tech and quantum ecosystem to accelerate real-world commercialization. By designing our architecture to interface with deployment engines like Deploy Quantum and foundation models from pioneers like First QFM, we ensure that our enterprise clients have a seamless, pragmatic transition from classical GPU-native solvers to hybrid and fault-tolerant QPU infrastructure.
Hardware-Agnostic Architecture
Our continuous JAX/XLA computational graph maps natively onto Parameterized Quantum Circuits — the same differentiable architecture targets CUDA-Q and PennyLane backends with no rewrite.
Dual-Use Thermal Physics
The identical Conjugate Heat Transfer (CHT) solver models AI data-center liquid cooling and cryogenic dilution-refrigerator cooling for quantum-computing hardware.
Sub-Microsecond QEC Decoding
Neural surrogates decode quantum error-correction syndromes at sub-microsecond latency — a 270× speedup over classical decoders, keeping pace with physical qubit cycle times.
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?
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