The world's fastest and most efficient AI for combinatorial optimization.

This page is a placeholder for people trying to figure out how Foxrane's optimizer actually works, and for OR-experts that are rightfully skeptical of hyperbolic AI claims. Quite soon, hopefully, we will be publishing benchmarks and technical documentation describing all our work in detail. In the meantime, the blurbs below will have to do.

Have you ever just sat and wondered whether the permutation and isometry invariance of the discrete Laplacian operator has some sort of fundamental connection to combinatorics? Of course not! Who sits and just things about that kind of stuff? You have to get your hands dirty and try things out by programming them!

Foxrane 9TAIL is a self-learning geometric transformer which, using linear time and memory, produces near-optimal solutions to exceptionally complex combinatorial problems. Notable design elements include Fourier Transform layers for scalable encoding, latent cross-attention layers for decoding, Laplacian positional encodings to capture full graph connectivity, and a system-dynamics network for predicting the optimality of long running Markov Decision Processes.

More details coming soon.