Building the future with high-performance Rust libraries for scientific computing, artificial intelligence, and quantum computing
Leading the Rust ecosystem in scientific and advanced computing
We develop enterprise-grade, open-source software libraries in Rust, bringing memory safety, performance, and fearless concurrency to scientific computing, AI, and quantum computing domains.
With over 10 million source lines of code across 30+ concurrent projects, we maintain one of the largest open-source Rust ecosystems focused on advanced computing solutions.
Tetsuya Kitahata, CEO and principal developer, leads our engineering efforts. All projects are publicly available on GitHub under permissive open-source licenses.
Production-ready libraries powering the next generation of computing
Comprehensive scientific computing and AI/ML foundation in Rust. SciPy-compatible API with Rust's performance, safety, and concurrency capabilities.
Rust-native semantic web platform. Alternative to Apache Jena/Fuseki with SPARQL 1.2 and GraphQL support from the same dataset.
PyTorch-compatible deep learning framework entirely in Rust. Tensor operations with sharding for distributed training.
Quantum computing framework with type-safe circuit design. Supports 30+ qubit simulations with SIMD and GPU acceleration.
High-performance Rust implementation of Hugging Face Transformers. 21+ architectures with 1.35x faster BERT inference.
High-performance numerical computing library inspired by NumPy. Foundation for scientific computing in Rust with ergonomic APIs.
Logic-to-tensor compiler transforming logical rules into tensor equations for neural-symbolic AI. Bridges symbolic reasoning with neural networks.
Pure-Rust neural speech synthesis framework. High-performance Text-to-Speech (TTS) with VITS, HiFi-GAN, and DiffWave vocoder.
scikit-learn reimplemented in Rust. Combines scikit-learn's intuitive API with Rust's performance and memory safety.
Comprehensive solutions across the computing spectrum
Linear algebra, FFT, signal processing, optimization, and numerical integration with SIMD acceleration
Neural networks, transformers, auto-differentiation, and graph processing for production ML
Circuit simulation, quantum algorithms, and hardware integration for quantum applications
SPARQL 1.2, GraphQL, RDF processing with AI-augmented reasoning capabilities
Visit our GitHub organization to see all 15+ projects, contribute, and join our community
GitHub: cool-japan