Making machine learning fast, useful, and accessible
We're closing the gap between building ML models and making them production-ready.
"To harness the full power of AI to improve lives, machine learning needs to be fast, useful, and accessible. Our mission is to make that happen."
Co-founder & CEO, OctoML
90% of ML projects don't make it to production
- Rapidly evolving ML frameworks
- Cambrian explosion of hardware backends
- Difficult to do comprehensive benchmarking
- Reliable model execution across platforms
10% that make it to production take months to deploy
- Labor-intensive packaging for devices and platforms
- No modern CI/CD integration to address model changes
- High CPU/GPU usage costs
Performance acceleration platform
Accelerate model performance while simplifying deployment.
Built on open-source Apache TVM, OctoML elevates performance, enables continuous deployment, and works seamlessly with PyTorch, TensorFlow, ONNX serialized models, and more.
Boost performance without losing accuracy.
Our proprietary process searches for the best program to automatically tune your model to the target hardware platform. Our customers have seen performance improvements of up to 30x.
Access comprehensive benchmarking.
Compare against the original model, similar public models, various CPU and GPU instance types, and evaluate device sizing to deploy on ARM mobile or embedded processors.
Relax knowing we’re future-proofed.
Our platform is built on open-source Apache TVM which is quickly becoming the defacto for machine learning compilers.
Experience broad interoperability.
OctoML works seamlessly with TensorFlow, Pytorch, TensorFlow-lite or ONNX serialized models, plus offers easy on-boarding of new and emergent hardware.
Enjoy automated deployment.
Easily deploy with a few command lines of code and skip the manual optimizations and save hours of expensive engineering time on manual optimization and performance testing.