Amazon SageMaker Autopilot

Amazon SageMaker Autopilot is ranked #15 of 37 in ML experiment tracking software on The Geeks Club. It runs on API, Web. There is no free plan. A free trial is offered.

Amazon SageMaker Autopilot plans and pricing

All plans

Amazon SageMaker AI pay-as-you-go Free Pay only for what you use; on-demand pricing has no minimum fees or upfront commitments. Autopilot-specific rate not stated · SageMaker AI Free Tier includes 160 hours/month of Canvas session time for the first 2 months aws.amazon.com · 30 Sept 2026

Compared on ML experiment tracking software

Free plan: No
Model-assisted labeling: Yes
Deployment options: cloud

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Amazon SageMaker Autopilot

Purpose: Autopilot automatically creates machine learning models with full visibility and is now in SageMaker Canvas.
Model building: It automatically builds, trains, and tunes models based on your data while providing control and visibility.
Prediction types: Autopilot infers whether data suits binary classification, multiclass classification, regression, or time series forecasting.
Model comparison: A leaderboard ranks generated models and shows performance metrics such as accuracy and precision.
Data preparation: It can fill missing data, provide statistical insights about dataset columns, and extract information from non-numeric columns.
Customization: Users can apply their own transformations alongside more than 300 preconfigured data transformations and customize data splits and training options.
Generated notebooks: Autopilot can generate a SageMaker Studio Notebook for a created model so users can inspect, refine, and recreate it.
Deployment: Models can be deployed to production with one click through SageMaker Canvas.
Integrations: SageMaker Studio lists Autopilot alongside SageMaker Pipelines, Experiments, Debugger, Model Monitor, Clarify, and JumpStart.
Pricing basis: SageMaker AI charges for usage, and its on-demand option has no minimum fees or upfront commitments.
Free tier: SageMaker AI’s Free Tier runs for the first two months from the first month a customer creates a SageMaker AI resource and includes 160 hours/month of Canvas session time.
Security: AWS describes its cloud security approach as combining security of the cloud infrastructure with security in the cloud through customer controls.
Compliance: AWS provides compliance information and resources for customers to understand AWS services’ compliance status.
Use cases: AWS describes use cases including price prediction, churn prediction, risk assessment, and time series forecasting.

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Where it ranks on The Geeks Club

Best ML Experiment Tracking Software in 2026#15 of 37
Best Predictive Analytics Software in 2026#10 of 35
Best Deep Learning Software in 2026#22 of 34
Best Model Registry Software in 2026#15 of 33
Best Data Science Platforms in 2026#17 of 32
Best AutoML Software in 2026#12 of 28
Best Data Preparation Software in 2026#8 of 27
Best MLOps Platforms in 2026#11 of 25
Best AI Image Annotation Tools in 2026#10 of 24
Best Data Labeling Software in 2026#13 of 24

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Sources

aws.amazon.com/sagemaker/ai/autopilot/· checked 30 Sept 2026
aws.amazon.com/sagemaker/ai/pricing/· checked 30 Sept 2026
aws.amazon.com/security/· checked 30 Sept 2026
aws.amazon.com/compliance/· checked 30 Sept 2026
aws.amazon.com/sagemaker/lakehouse/· checked 28 Sept 2026
aws.amazon.com/sagemaker/ai/experiments/· checked 28 Sept 2026