Deploy production-ready models with one line of Python
Baseten is the MLOps platform for startups to rapidly develop, deploy, and test models in production.
Trusted by top data science and machine learning teams
Straightforward deploys, in one place
Deployment shouldn't mean becoming a Kubernetes expert. Instantly deploy models from any training environment with one line of Python, while keeping versions and inference centralized.
"Baseten provides us with all of the speed and control of self-serving our model deployment without any of the annoying config, infra, and health checks."
Deploy models in-line, using your preferred training environment
Set global system packages and settings to run models from anywhere, by anyone
Track model artifacts and training metadata with every new model version
Ship production-ready APIs, fast
Models deployed to Baseten are put behind a REST API for immediate use in production. Auto-scaling resources ensure efficient, low-latency performance even in high-traffic scenarios.
"Baseten gets the process of tool-building out of the way so we can focus on our key skills: modeling, measurement, and problem solving."
Scale up or down automatically to handle increased traffic, efficiently
Deploy to a GPU instantly. Warm starts ensure fast availability
Comprehensive logs ensure you can quickly debug any issues
Works with any model framework.
Built on open source.
Baseten is built on Truss, an open-source standard for packaging models built in any framework. Share and deploy to any environment, locally or in-production.
Accelerate iteration cycles between model versions with robust model monitoring, drift detection, and A/B testing.
"Baseten provides an easy way for us to host our models, iterate on them, and experiment without worrying about any of the DevOps involved."
Gain insight into your model's traffic and resource utilization in real-time
Set custom conditions and get alerts when your model's drift is too large
Test multiple versions simultaneously to optimize for model performance