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What is Enzai?
An AI governance platform developed by legal experts specializing in regulatory issues, tailored to meet your unique requirements and policies, is essential for organizations. As businesses navigate the ever-evolving landscape of legislation and regulations, they must remain vigilant in their compliance efforts. Failure of AI systems can lead to a breakdown in customer trust and diminished user interaction with products. The increasing intricacy of AI technologies, which now encompass a wider spectrum of applications than ever, poses significant challenges for teams. Our platform offers assessments and real-time monitoring tools to help ensure that your AI systems remain compliant, enabling users to receive timely alerts about potential risks or concerns that could adversely affect operations. While implementing effective AI governance can be a time-consuming endeavor, our automated features facilitate the seamless integration of model data and documentation, simplifying the processes of review and updates. Understanding AI compliance is vital across all levels of your organization, and it is important that senior leaders have access to thorough insights on compliance matters to support informed decision-making and appropriate dissemination of reports. We offer a comprehensive suite of policies that ensure adherence to legal and regulatory standards through our pre-configured assessments. Furthermore, our platform promotes continuous education and training, keeping all team members abreast of the latest trends and practices in AI governance and compliance. By investing in these resources, organizations can cultivate a culture of compliance that enhances their overall operational integrity and stakeholder confidence.
What is Azure Machine Learning?
Optimize the complete machine learning process from inception to execution. Empower developers and data scientists with a variety of efficient tools to quickly build, train, and deploy machine learning models. Accelerate time-to-market and improve team collaboration through superior MLOps that function similarly to DevOps but focus specifically on machine learning. Encourage innovation on a secure platform that emphasizes responsible machine learning principles. Address the needs of all experience levels by providing both code-centric methods and intuitive drag-and-drop interfaces, in addition to automated machine learning solutions. Utilize robust MLOps features that integrate smoothly with existing DevOps practices, ensuring a comprehensive management of the entire ML lifecycle. Promote responsible practices by guaranteeing model interpretability and fairness, protecting data with differential privacy and confidential computing, while also maintaining a structured oversight of the ML lifecycle through audit trails and datasheets. Moreover, extend exceptional support for a wide range of open-source frameworks and programming languages, such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, facilitating the adoption of best practices in machine learning initiatives. By harnessing these capabilities, organizations can significantly boost their operational efficiency and foster innovation more effectively. This not only enhances productivity but also ensures that teams can navigate the complexities of machine learning with confidence.
Integrations Supported
APERIO DataWise
Azure Container Registry
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Kinect DK
Azure Marketplace
Azure Percept
Cranium
IBM watsonx.data
Kedro
Integrations Supported
APERIO DataWise
Azure Container Registry
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Kinect DK
Azure Marketplace
Azure Percept
Cranium
IBM watsonx.data
Kedro
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
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
Enzai
Company Location
Ireland
Company Website
www.enz.ai/
Company Facts
Organization Name
Microsoft
Date Founded
1975
Company Location
United States
Company Website
azure.microsoft.com/en-us/services/machine-learning/
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
