Baseten

Baseten is a machine learning infrastructure that provides all the necessary tools to deploy and serve ML models efficiently, scalably, and cost-effectively. It offers optimized serving for open-source models as well as your own models. Baseten is highly performant infra that scales with you, providing reliable logging and monitoring for every model deployed.

Key Features:

1. Model Deployment: Deploy best-in-class open-source models or take advantage of optimized serving for your own models.

2. Autoscaling: Horizontally scalable service that automatically scales up to keep up with traffic increases without extra configuration required.

3. Faster Pipeline Optimization: Optimized pipeline building images, starting containers and caching models, provisioning resources, and fetching weights ensures quick scaling from zero to ready for inference.

4. Logs & Metrics: Provides reliable logging and monitoring for every model deployed to ensure visibility into what's happening under the hood at every step.

5. Customization: Customize the infrastructure running your model by selecting an instance type or deploying on your own infrastructure.

Use Cases:

- Startups can use their AWS or GCP credits on Baseten while enterprises can self-host it inside any modern cloud without needing their data to leave their VPCs.

- Patreon saved nearly $600k/year in ML resources using Baseten while Laurel ships ML models 9+ months faster leveraging sophisticated ML models.

In conclusion, Baseten is a powerful tool that simplifies machine learning deployment processes by offering efficient scalability options along with reliable logging and monitoring features. Its customization feature allows users to select an instance type or deploy on their own infrastructure while startups can utilize their AWS or GCP credits on it too!