We provide the first Physics-Informed Geometric Engine that replaces stochastic Monte Carlo methods with deterministic topology. Achieve 100x faster material screening and financial risk modeling with zero hallucination.
A proprietary suite of solvers powered by the IGM-RG™ Kernel. Solving governing equations across Quantum, Fluid, Material, and Financial domains.
Hardware-Aware Pulse Control. Mitigate decoherence in superconducting qubits. Our engine optimizes gate topology and pulse shaping instantly, replacing lengthy Monte Carlo calibration loops.
Mesh-Independent CFD. Solves high-Reynolds flows using geometric regularization instead of brute-force meshing. Ensures numerical stability in pipeline and aerodynamic simulations with significantly lower compute costs.
High-Throughput Material Discovery. Predict molecular stability and breakdown voltages for battery electrolytes. Our geometric rigidity metric ($\kappa_c$) identifies viable candidates before expensive lab synthesis begins.
Arbitrage-Free Pricing Engine. Applies Riemannian geometry to option pricing surfaces. Eliminates the calibration noise of the Heston model, preventing negative probability estimates in high-volatility regimes.
Traditional AI relies on data-hungry neural networks that can hallucinate. IA WOLF builds intelligence on First Principles.
We use the same Renormalization Group (RG) equations to model electron flow in a battery and cash flow in a market. One mathematical core, infinite applications.
Monte Carlo rolls dice. We solve the manifold. This provides exact, reproducible results for regulatory compliance and safety-critical engineering.