A lean, layered pipeline where English prompts enter at the top, emerging as GPU-accelerated decisions at the bottom—every step auditable and evolvable.
Express problems as concise chains like D_m(5k) → C*(60,30m) → O*(50). Each token is a handle to GPU primitives.
No eager loops—symbols auto-fuse (distance + contraction = single kernel launch). Data stays GPU-resident.
MetaLearner analyzes runs and invents hybrids like O* = 2opt ⊗ swap (22% faster). System self-evolves.
Parse problems as DAGs. When data changes (+100 orders), re-execute only downstream symbols in <50ms.
Provably correct solutions verified by mathematical proofs, not heuristics or approximations.
148 symbols span optimization, transformers, SSMs, GNNs, forecasting, and diffusion models.
Each solver optimized for specific problem characteristics. Choose the right tool for your workload.
Core Two-Phase Architecture
Combines constraint programming for hard constraints with GPU-accelerated neural constraint optimization for soft constraints.
VRP-Optimized
Uses biological metaphors (DNA codons → amino acids → proteins) to create fast, interpretable Vehicle Routing Problem solutions.
Quality Enhancement
Parallel exploration of multiple solution space regions to find high-quality solutions with statistical confidence.
Fast Updates
Efficiently solves modified problems by reusing computation from previous solutions, enabling real-time adjustments.
Benchmarks against industry-standard alternatives.
All solutions are mathematically verified to satisfy every hard constraint. No approximations, no violations.
Unlike LLMs which can hallucinate, our outputs are verified by mathematical proofs. Enterprise-grade reliability.
Fused tensor kernels deliver 10-50x speedups. Real-time performance at scale on modern hardware.
7-patent fortress covering symbology, composites, streaming, and evolution. Defensible moat.