Quantum Bridge AI
Quantum Bridge AI provides a physics engine for industrial intelligence that automates CAD-to-solve workflows, delivering bitwise-deterministic CFD and FEA simulation results in minutes rather than days. The platform uses stiff differentiable physics solvers and neural surrogates to achieve 100–1000× speedups over legacy solvers while maintaining machine-precision fidelity at 10⁻¹⁴. Its no-code CAD ingestion accepts .STL and .STEP geometry and auto-generates validated solver configurations.
- Manufacturing / Industry 4.0
- Artificial Intelligence
- AI Agents
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Legacy CFD and FEA simulation solvers are computationally prohibitive for real-time industrial optimization, often requiring multi-day render times. This forces engineering teams to rely on empirical trial-and-error methods, slowing down product development cycles and limiting the ability to explore design alternatives rapidly.
Solution
Quantum Bridge AI provides a physics engine for industrial intelligence that automates CAD-to-solve workflows and delivers bitwise-deterministic simulation results in minutes rather than days. The platform ingests raw CAD geometry, auto-generates validated solver configurations, and routes cases to the appropriate JAX-based solver via LLM agents bound by schema contracts. Neural surrogates and stiff differentiable physics solvers achieve machine-precision fidelity with 100–1000× speedups over legacy FEM and CFD solvers, while interactive in-browser visualization enables sub-second thermal, flow, and stress field exploration. The entire computational graph is end-to-end differentiable, enabling exact gradient-based optimal control for industrial optimization workflows.
Target Audience
Primary customers are industrial operators and engineering teams in aerospace, manufacturing, and quantum infrastructure sectors that require high-fidelity, deterministic simulation for design optimization and mission-critical workflows.
Features
- Axiom Engine: stiff differentiable physics solvers with implicit-explicit time stepping that resolve stiff reaction-diffusion dynamics at 10⁻¹⁴ precision
- Laminar-GND: continuous-graph gradient method with BCOO sparse Laplacian representation achieving O(1) memory with solver depth and zero over-smoothing
- No-code CAD ingestion supporting .STL and .STEP geometry with auto-generated solver .json configuration
- Constrained multi-agent orchestration with LLM-in-the-loop workflow routing, bound by typed data contracts to eliminate hallucinations in schema validation
- Bitwise-deterministic solver trajectories (Max Diff = 0.0) with glass-box physical traceability linking every result to an interpretable governing equation
- Encrypted inference pipeline using TenSEAL CKKS homomorphic encryption with divergence maintained at ~9.5 × 10⁻⁷
- Agent-based routing with human-in-the-loop control for mission-critical decision gating