Faster Code, Zero Rewrites
Kai automatically generates optimized versions of your code, benchmarks them, and delivers the fastest one as a ready-to-merge PR.
From Repo to Better Code in Minutes
You set the goal. Kai finds the fastest path there in minutes.
GSO Benchmark Results
We test Kai Evolve on compatible tasks from GSO benchmark of 100+ real-world optimization tasks across major open source projects. Evolve beats human expert commits in most cases including the examples below.
Boolean lookup table for integer isin — O(1) lookups instead of O(n log n) sorting
Replaced inspect.stack() with sys._getframe() and merged two helpers into one
Optimized group iteration and reduced redundant checks in processing loop
8 Showcases Across Domains
GPU Kernels
192x Faster NVIDIA B200 FP4
Sorting Networks
98x Faster Than stdlib
SAT Solver Heuristics
3.2x Faster Satisfiability
Matrix Multiplication
Novel Strassen Variant
Hash Functions
Near-Perfect Distribution
Neural Network Pruning
4.1x Inference Speedup
Uniswap v4 SwapMath
Gas Optimization on Production DeFi
NetworkX Betweenness
1724x Faster Graph Centrality
[ GPU Optimization ]
540 iterationsGPU Kernels — 192x Faster NVIDIA B200 FP4
Evolved a custom CUDA kernel for NVIDIA B200 FP4 matrix operations. The initial implementation used naive memory access patterns — Kai Evolve discovered coalesced memory layouts and warp-level primitives that humans hadn't considered.
[ Algorithm Discovery ]
320 iterationsSorting Networks — 98x Faster Than stdlib
Starting from a standard comparison-based sort, Kai Evolve discovered a SIMD-optimized sorting network that outperforms the standard library by 98x on fixed-size arrays. The evolved solution uses bitonic merge patterns never seen in textbooks.
[ Constraint Solving ]
410 iterationsSAT Solver Heuristics — 3.2x Faster Satisfiability
Evolved the variable selection heuristic for a DPLL-based SAT solver. The standard VSIDS strategy was replaced with a novel activity-decay scheme that adapts clause learning rates based on conflict graph topology.
[ Linear Algebra ]
890 iterationsMatrix Multiplication — Novel Strassen Variant
Discovered a new decomposition for 4x4 matrix multiplication that reduces the number of scalar multiplications below Strassen's bound. The evolved algorithm uses 47 multiplications instead of the naive 64.
[ Data Structures ]
260 iterationsHash Functions — Near-Perfect Distribution
Evolved a non-cryptographic hash function optimized for hash table use. Starting from FNV-1a, Kai Evolve discovered a mixing function that achieves near-perfect avalanche properties with fewer operations.
[ ML Optimization ]
380 iterationsNeural Network Pruning — 4.1x Inference Speedup
Evolved a structured pruning strategy for ResNet-50 that removes 78% of parameters while maintaining 98.2% of the original accuracy. The evolved masks discover layer-specific sparsity patterns that uniform pruning misses.
[ Smart Contracts ]
197 iterationsUniswap v4 SwapMath — Gas Optimization on Production DeFi
Optimized the core computeSwapStep function in Uniswap v4 — already hand-tuned by world-class Solidity engineers across three major versions. Evolution discovered assembly-level variable initialization and pre-computed fee complements, saving ~$6.2M/year at scale.
[ Graph Analytics ]
100 iterationsNetworkX Betweenness — 1724x Faster Graph Centrality
Optimized NetworkX's pure-Python betweenness centrality (Brandes' algorithm) by replacing dict-based structures with pre-allocated arrays, manual queue indexing, and selective resets. 100% correctness preserved across all graph types.
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