BasetenBaseten simplifies ML model deployment with a powerful serverless infrastructure, making production-ready AI accessible for developers.

Baseten is a serverless platform designed for deploying and scaling machine learning models efficiently. It provides developers with infrastructure to easily integrate AI into production applications.

Baseten is a platform for deploying and scaling machine learning models as serverless endpoints. It simplifies the process of getting AI models into production, offering infrastructure and tools for developers.

Not yet. This listing is compiled from Baseten’s public documentation, pricing pages and changelogs — nothing on this page is presented as a hands-on test result.Baseten sits in our testing queue; when we run it, this section will state what we tested, how long for, and what it actually produced. How we review AI tools.

• Real-time Inference: Deploy models for immediate predictions, such as image recognition or natural language processing, accessible via APIs.
• Batch Processing: Run ML models on large datasets asynchronously for tasks like data analysis or report generation.
• AI-powered Applications: Integrate machine learning capabilities directly into web or mobile applications to enhance user experiences.
• Prototyping and Experimentation: Quickly deploy and test new models without managing complex infrastructure.

• Serverless API endpoints for ML models
• Automated scaling
• Model versioning and management
• Built-in monitoring and logging
• Support for various ML frameworks
• CI/CD integration

Prices as of July 25, 2026, taken from Baseten’s public pricing page. Vendors change pricing without notice — check before you buy.

• Specific compute or runtime environment constraints
• Potential vendor lock-in for deep integrations

• AWS SageMaker
• Google Cloud AI Platform
• Azure Machine Learning
• Hugging Face Inference Endpoints

1. Sign up for a Baseten account and access the platform.
2. Upload your trained machine learning model and define its input/output schema.
3. Deploy your model as a serverless API endpoint and integrate it into your application.

Use a SynaBot assistant to produce the thinking, then move the output into Baseten for execution. Every SynaBot assistant is free to try on the Lite plan.

• Content Creator (ZARA) — drafts the copy, captions and campaign angles you'll run through Baseten.
• Business Planner (VIKRAM) — decides whether Baseten belongs in your stack and what it should replace.
• Project Manager (PACE) — turns the rollout of Baseten into owned, dated tasks.

Browse the full AI assistant roster, grab a starting point from the prompt library, or have us wire it together with our AI consultancy service.