About NeurFly

Our mission is to make neural network automation accessible to every engineering team on the planet.

Built by Researchers, for Engineers

NeurFly was founded in 2024 by Dr. Elena Volkov, following a decade of neural architecture research at MIT and DeepMind. The core insight was simple: the techniques that let top AI labs build production-quality models — automated architecture search, differentiable optimization, hardware-aware compilation — were locked away behind academic papers and complex codebases inaccessible to most engineering teams.

Elena assembled a team of ML engineers and infrastructure experts who shared one conviction: that every engineering team deserves access to the tools that define the frontier of AI. NeurFly was built to bridge that gap — translating peer-reviewed research into production-ready software any engineer can use.

Today, NeurFly's platform is used by engineering teams at companies ranging from fast-growing startups to established technology leaders. Our customers report 90% reductions in model development time and 300% improvements in training efficiency compared to building models manually.

NeurFly founding story — neural network research lab

Democratizing Deep Learning

NeurFly exists to remove the barriers that prevent most engineering teams from building production-quality neural networks.

Accessibility

Neural network automation — the kind that runs differentiable architecture search and hardware-aware compilation — should not be limited to organizations that can hire dozens of ML PhDs. NeurFly makes this expert-level tooling available to every engineering team.

Research-Backed

Every feature in NeurFly is grounded in peer-reviewed research. We translate the latest advances in AutoML and neural architecture search into practical engineering tools.

Reproducibility

Science requires reproducibility. Every experiment, every model, every result in NeurFly is fully tracked and reproducible — giving teams confidence in their AI systems.