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What is Concentio?

Analyzing data from a wide range of IoT sources, including sensors and devices, provides users with both predictive and prescriptive insights that enable them to tackle potential anomalies in real time. The Concentio® IoT Doctor efficiently processes data from various IoT endpoints, alerting users to any incoming faulty data to ensure issues are addressed before the information is used for further analysis. Furthermore, the Concentio® Production Line Fault Prediction tool utilizes AI to perform predictive evaluations of production line components by examining IoT data, videos, and images. In addition, Concentio® Optimal Asset Management evaluates incoming data from a network of utility service assets, empowering users to plan maintenance proactively and significantly lower capital expenditures by guiding strategic asset replacement decisions. This holistic approach not only boosts operational efficiency but also greatly enhances both asset longevity and overall performance, ultimately leading to a more resilient operational framework. By integrating these advanced tools, organizations can ensure they are prepared for any challenges that may arise.

What is AWS IoT Analytics?

The information produced by IoT devices is largely unstructured, which poses significant difficulties for conventional analytics and business intelligence systems that are designed primarily for structured data. These devices collect data from various noisy environments, such as temperature fluctuations, motion detection, and sound levels, resulting in common problems like data gaps, message corruption, and unreliable readings that require extensive cleaning prior to any substantial analysis. Moreover, the value of IoT data often hinges on its integration with external data sources from third parties. For example, irrigation systems in vineyards can improve moisture sensor readings through the inclusion of rainfall data, allowing farmers to refine their water use and boost crop productivity effectively. To facilitate the analysis of data generated by IoT devices, AWS IoT Analytics simplifies each intricate step in the process. This fully managed service operates on a pay-as-you-go basis, allowing it to effortlessly scale to accommodate varying requirements while also streamlining the overall data analysis procedure. By utilizing such automated solutions, companies can more effectively extract critical insights from their IoT data, ultimately leading to better decision-making and improved operational efficiency. In this way, organizations can harness the potential of their IoT investments to drive innovation and growth.

Media

Media

Integrations Supported

AWS App Mesh
AWS IAM Identity Center
Oracle Database@AWS

Integrations Supported

AWS App Mesh
AWS IAM Identity Center
Oracle Database@AWS

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$3.43 per month
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

Scry AI

Date Founded

2014

Company Location

United States

Company Website

scryai.com

Company Facts

Organization Name

Amazon Web Services

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/iot-analytics/

Categories and Features

IoT Analytics

Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking

Preventive Maintenance

Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management

Categories and Features

Asset Tracking

Activity Tracking
Audit Trails
Barcoding / RFID
Checkout / Check-In
Depreciation Tracking
Disposal Tracking
Inventory Management
Location Tracking
QR Codes
Reservations
Service History

EAM

CMMS
Energy Management
Equipment Management
Facility Management
IT Asset Management
Inventory Management
Maintenance Management
Parts Management
Preventive Maintenance Scheduling
Software License Management
Warranty Management
Work Order Management

Equipment Maintenance

Customer Database
Dispatch Management
Equipment Tracking
Inventory Control
Job Management
Maintenance Scheduling
Warranty Tracking
Work Order Management

IoT Analytics

Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking

IT Asset Management

Asset Tracking
Audit Management
Compliance Management
Configuration Management
Contract/License Management
Cost Tracking
Depreciation Management
IT Service Management
Inventory Management
Maintenance Management
Procurement Management
Requisition Management
Supplier Management

Maintenance Management

Asset Tracking
Billing & Invoicing
Calibration Management
Dispatch Management
Inventory Control
Inventory Management
Key & Lock Management
Mobile Access
Planning Calendar
Predictive Maintenance
Preventive Maintenance
Purchasing
Scheduling
Service History Tracking
Technician Management
Work Order Management

Preventive Maintenance

Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management

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