Research
Portable Machine Learning
Combining WebAssembly's speed with AI's adaptability to create lightweight models that run directly in browsers at native-speed efficiency.
Our Mission
At ελβίξα, we're redefining computational boundaries by creating high-performance applications that run seamlessly across platforms. Our research combines the speed of WebAssembly with the intelligence of machine learning to build the next generation of web technologies.
wasm
WebAssembly
Breaking performance barriers with portable, sandboxed execution across all platforms
ai
AI Innovation
Building intelligent systems that learn and adapt to real-world challenges
🌐
Open Innovation
Fostering open-source collaboration to accelerate global technological progress
Featured Research
Tech Update
New Optimization Algorithms
Pioneering memory-efficient WebAssembly compilers that reduce binary sizes by 40% while maintaining full performance parity across all platforms.
Our Team
Dr. Elena Markov
Lead WebAssembly Architect
Principal architect behind ελβίξα's WebAssembly compiler optimizations with 15+ years of low-level systems programming experience.
Anika Sharma
Machine Learning Lead
Dr. Sharma's research in neural compilation has produced groundbreaking results in model inference optimization for WebAssembly.
Luca Moretti
Performance Engineer
Expert in creating high-performance algorithms with a focus on real-time computation across heterogeneous computing platforms.