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What is Lanai?
Lanai operates as a platform designed to empower organizations by helping them tackle the complexities of integrating AI into their operations, offering vital insights into AI interactions, safeguarding sensitive information, and streamlining the execution of successful AI initiatives. Its suite of features includes AI visibility to reveal prompt interactions across diverse applications and teams, risk monitoring for compliance assurance and vulnerability detection, and progress tracking to measure adoption against strategic goals. Additionally, Lanai provides users with policy intelligence and protective measures to ensure the security of confidential data and adherence to regulations, along with in-context safeguards and guidance to facilitate appropriate query routing without compromising document integrity. To enhance the user experience further, the platform offers smart prompt coaching for on-the-spot assistance, customized insights into top use cases and applications, as well as detailed reporting for both management and end-users, ultimately driving enterprise adoption and optimizing return on investment. By bridging the gap between AI functionality and corporate requirements, Lanai aspires to cultivate a culture of innovation and operational efficiency within organizations, empowering them to fully leverage the potential of AI technology. In doing so, it positions itself as a pivotal resource for enterprises looking to thrive in the rapidly evolving landscape of artificial intelligence.
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 Data Science Virtual Machines
Azure Database for MariaDB
Azure Kinect DK
Azure Marketplace
BotCore
Canva
Freshsales
Gemini
HubSpot CRM
Integrations Supported
APERIO DataWise
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Kinect DK
Azure Marketplace
BotCore
Canva
Freshsales
Gemini
HubSpot CRM
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
Lanai
Date Founded
2024
Company Location
United States
Company Website
www.withlanai.com
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
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
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
