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What is Gate22?

Gate22 functions as a comprehensive platform for AI governance and Model Context Protocol (MCP) control that is tailored for enterprises, providing centralized management of the security and oversight of AI tools and agents interacting with MCP servers. It enables administrators to onboard, configure, and manage both internal and external MCP servers, offering granular permissions at the functional level, team-oriented access controls, and role-specific policies to guarantee that only approved tools and capabilities are accessible to the appropriate teams or individuals. By delivering a unified MCP endpoint, Gate22 consolidates multiple MCP servers into an easily navigable interface with just two main functions, which helps to lessen token consumption for developers and AI clients while effectively reducing context overload and maintaining both accuracy and security. The platform features an administrative interface with a governance dashboard that tracks usage patterns, ensures compliance, and applies least-privilege access, while the member interface streamlines and secures access to authorized MCP bundles. This dual perspective not only enhances operational productivity but also fortifies the overall security infrastructure within the organization. Additionally, the integration of these functionalities fosters a collaborative environment where teams can work more effectively while adhering to compliance standards.

What is Amazon SageMaker?

Amazon SageMaker is a robust platform designed to help developers efficiently build, train, and deploy machine learning models. It unites a wide range of tools in a single, integrated environment that accelerates the creation and deployment of both traditional machine learning models and generative AI applications. SageMaker enables seamless data access from diverse sources like Amazon S3 data lakes, Redshift data warehouses, and third-party databases, while offering secure, real-time data processing. The platform provides specialized features for AI use cases, including generative AI, and tools for model training, fine-tuning, and deployment at scale. It also supports enterprise-level security with fine-grained access controls, ensuring compliance and transparency throughout the AI lifecycle. By offering a unified studio for collaboration, SageMaker improves teamwork and productivity. Its comprehensive approach to governance, data management, and model monitoring gives users full confidence in their AI projects.

Media

Media

Integrations Supported

AWS Clean Rooms
AWS Deep Learning Containers
AWS EC2 Trn3 Instances
AWS IoT Core
AWS Step Functions
Amazon EC2 G5 Instances
Amazon EC2 P4 Instances
Amazon EC2 P5 Instances
Amazon S3 Express One Zone
Amazon SageMaker Clarify
Cranium
DataHub
Datasaur
Deep Lake
Flyte
JFrog ML
Label Studio
Model Context Protocol (MCP)
Pruna AI
StrongDM

Integrations Supported

AWS Clean Rooms
AWS Deep Learning Containers
AWS EC2 Trn3 Instances
AWS IoT Core
AWS Step Functions
Amazon EC2 G5 Instances
Amazon EC2 P4 Instances
Amazon EC2 P5 Instances
Amazon S3 Express One Zone
Amazon SageMaker Clarify
Cranium
DataHub
Datasaur
Deep Lake
Flyte
JFrog ML
Label Studio
Model Context Protocol (MCP)
Pruna AI
StrongDM

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

ACI.dev

Company Location

United States

Company Website

gate22-docs.aci.dev/introduction/overview

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/

Categories and Features

Categories and Features

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Popular Alternatives

Popular Alternatives