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Description
Amazon SageMaker Studio serves as a comprehensive integrated development environment (IDE) that offers a unified web-based visual platform, equipping users with specialized tools essential for every phase of machine learning (ML) development, ranging from data preparation to the creation, training, and deployment of ML models, significantly enhancing the productivity of data science teams by as much as 10 times. Users can effortlessly upload datasets, initiate new notebooks, and engage in model training and tuning while easily navigating between different development stages to refine their experiments. Collaboration within organizations is facilitated, and the deployment of models into production can be accomplished seamlessly without leaving the interface of SageMaker Studio. This platform allows for the complete execution of the ML lifecycle, from handling unprocessed data to overseeing the deployment and monitoring of ML models, all accessible through a single, extensive set of tools presented in a web-based visual format. Users can swiftly transition between various steps in the ML process to optimize their models, while also having the ability to replay training experiments, adjust model features, and compare outcomes, ensuring a fluid workflow within SageMaker Studio for enhanced efficiency. In essence, SageMaker Studio not only streamlines the ML development process but also fosters an environment conducive to collaborative innovation and rigorous experimentation.
Amazon SageMaker Unified Studio provides a seamless and integrated environment for data teams to manage AI and machine learning projects from start to finish. It combines the power of AWS’s analytics tools—like Amazon Athena, Redshift, and Glue—with machine learning workflows.
Description
Sage2 is a cloud-based AI model and API tailored for developers who are creating software agents and automating workflows. It processes structured task instructions and generates decisions or information in formats that machines can easily interpret, enabling applications to assign tasks like classification, routing, evaluation, and data extraction to a model specifically designed for tool-utilizing agents. Developers have the option to interact with Sage through its API, examine model functionality via browser demos, and integrate it into their agent development environments, such as Cursor and Claude Code. The service features a pricing structure for API usage that includes a free tier alongside various paid monthly plans, with usage fees and included credits differing based on the selected plan. Sage is primarily targeted at individual developers and software teams seeking to enhance their applications with decision-making and extraction functionalities without the need to manage the model independently. This flexibility allows for streamlined integration into existing workflows, making it an appealing choice for those looking to leverage AI capabilities effectively.
API Access
Has API
No
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
AWS Glue
Yes
Amazon EMR
Yes
Amazon SageMaker
Yes
Amazon SageMaker Data Wrangler
Yes
Amazon SageMaker Debugger
Yes
Amazon Web Services (AWS)
Yes
Claude Code
No
Cursor
No
Jupyter Notebook
Yes
PyTorch
Yes
Integrations
AWS Glue
No
Amazon EMR
No
Amazon SageMaker
No
Amazon SageMaker Data Wrangler
No
Amazon SageMaker Debugger
No
Amazon Web Services (AWS)
No
Claude Code
Yes
Cursor
Yes
Jupyter Notebook
No
PyTorch
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$0
The Free plan costs $0/month and includes $0.20 in usage. The Developer plan costs $14/month and includes $14 in usage. Additional usage is charged by token and web-search rates shown on the pricing page.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/studio/
Vendor Details
Company Name
Levanto Labs
Founded
2026
Country
United States
Website
levanto.ai/model
Product Features
IDE
Code Completion
No
Compiler
No
Cross Platform Support
No
Debugger
No
Drag and Drop UI
No
Integrations and Plugins
No
Multi Language Support
No
Project Management
No
Text Editor / Code Editor
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
