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What is Sage?

Sage equips communities with the tools needed to collect important data while also allowing them to derive insights that improve key business metrics. Its modern, cohesive interface simplifies the diverse array of tools used by caregivers, enhancing communication and fostering a more knowledgeable, efficient, and collaborative care environment. Residents gain from an easy-to-navigate, real-time alert system that guarantees they receive necessary assistance or care at precisely the right moment. This innovative technology not only connects care teams via the application but also compiles essential data that fuels analytics and generates valuable insights. With Sage’s accessible platform, community teams can effectively prioritize and manage crucial daily support tasks tailored to resident needs, which ultimately leads to improved outcomes and experiences for those being served. The platform boasts a dynamic dashboard that delivers all-encompassing data regarding care and operations, allowing for immediate access to insights on resident care necessities and community performance metrics, along with actionable guidance and efficient reporting tools. By adopting this comprehensive strategy to data and care management, Sage stands out as a vital resource for communities aspiring to enhance their service quality and ensure that every resident’s needs are met promptly and effectively. Additionally, the integration of such technology promises to create a more responsive and adaptive care environment, further solidifying Sage's value in modern caregiving settings.

What is Amazon SageMaker Clarify?

Amazon SageMaker Clarify provides machine learning practitioners with advanced tools aimed at deepening their insights into both training datasets and model functionality. This innovative solution detects and evaluates potential biases through diverse metrics, empowering developers to address bias challenges and elucidate the predictions generated by their models. SageMaker Clarify is adept at uncovering biases throughout different phases: during the data preparation process, after training, and within deployed models. For instance, it allows users to analyze age-related biases present in their data or models, producing detailed reports that outline various types of bias. Moreover, SageMaker Clarify offers feature importance scores to facilitate the understanding of model predictions, as well as the capability to generate explainability reports in both bulk and real-time through online explainability. These reports prove to be extremely useful for internal presentations or client discussions, while also helping to identify possible issues related to the model. In essence, SageMaker Clarify acts as an essential resource for developers aiming to promote fairness and transparency in their machine learning projects, ultimately fostering trust and accountability in their AI solutions. By ensuring that developers have access to these insights, SageMaker Clarify helps to pave the way for more responsible AI development.

Media

Media

Integrations Supported

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Childcare online Booking
Longview Transfer Pricing
TelecomBilling.Net

Integrations Supported

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Childcare online Booking
Longview Transfer Pricing
TelecomBilling.Net

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

Sage

Date Founded

2020

Company Location

United States

Company Website

www.hellosage.com

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/sagemaker/clarify/

Categories and Features

Assisted Living

Admissions Management
Billing & Invoicing
Building Maintenance
Care Planning
Event / Activities Planning
Incident Management
Marketing / Lead Management
Meal / Nutrition Management
Medical Records
Medication Tracking
New Resident Assessment
Resident Info Management
Scheduling
Staff Management
Work Order Management

Categories and Features

Machine Learning

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

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