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Alternatives to Consider
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TRACTIANTractian serves as the Industrial Copilot focused on enhancing maintenance and reliability by integrating both hardware and software to oversee asset performance, streamline industrial operations, and execute predictive maintenance approaches. The platform, powered by AI, enables companies to avert unexpected equipment failures and improve production efficiency. Headquartered in Atlanta, GA, Tractian also has a global footprint with branches in Mexico City and Sao Paulo, thereby expanding its reach. For more information, you can visit their website at tractian.com, where additional resources and details about their offerings are available.
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The Asset Guardian EAM (TAG)The Asset Guardian (TAG) Mobi is the chosen preventive maintenance and asset management solution (EAM) for Microsoft Dynamics 365 Business Central, designed to deliver reliable manufacturing asset solutions that reduce risk and downtime. TAG Mobi prevent downtime, maximize asset performance, and accelerate onboarding and training with the support of AI tools and intuitive dashboards. No silos. No extra software. Just smooth integration and quick adoption—so maintenance teams can work faster, and managers get the data they need to make decisions.
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Epicor Connected Process ControlEpicor Connected Process Control offers an intuitive software solution designed to create and manage digital work instructions while maintaining strict process control, effectively minimizing the chances of errors in operations. By integrating IoT devices, it captures comprehensive time studies and detailed process data, including images, at the task level, providing unprecedented real-time visibility and quality oversight. The eFlex system is versatile enough to accommodate countless product variations and thousands of components, catering to both component-based and model-based manufacturers alike. Furthermore, work instructions seamlessly connect to the Bill of Materials, guaranteeing that products are assembled correctly every time, even when modifications occur during production. This advanced system intelligently adapts to variations in models and components, ensuring that only the relevant work instructions for the current build at the station are presented, enhancing efficiency and accuracy throughout the manufacturing process. In this way, Epicor empowers manufacturers to maintain high standards of quality control while adapting to the dynamic nature of production demands.
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AizonAizon: Intelligent GxP Manufacturing Aizon delivers an AI-powered platform that redefines how pharmaceutical and biotech manufacturers operate under GxP requirements. Our solutions empower teams to enhance efficiency, raise yields, and maintain the highest standards of product quality. - Aizon Execute — Intelligent Batch Record (iBR): Digitize production quickly to reduce manual errors, lower deviations, and accelerate the release of compliant batches. - Aizon Unify — Contextualized Intelligent Lakehouse: Connect and contextualize data from diverse sources to improve decision-making and achieve operational excellence. - Aizon Predict — GxP AI Industrialization: Use predictive AI models to fine-tune critical process parameters, increase Right-First-Time outcomes, and deliver higher manufacturing performance. Aizon enables manufacturers to move beyond traditional compliance and embrace true operational intelligence—learning from the past, acting decisively in the present, and innovating for the future.
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EvoconEvocon is a cloud-based solution designed for monitoring production, assisting manufacturing firms in enhancing their operational efficiency. By automating and digitizing the process of gathering data from production machines, Evocon ensures that this information is seamlessly transferred to the cloud, allowing manufacturers to access it in real-time, whether they are on-site or working remotely. Furthermore, the platform visualizes this data in a user-friendly manner, making it actionable for users. This capability enables manufacturers to monitor downtime, minimize costs, and optimize their production equipment usage effectively. Additionally, it provides a foundation for informed decision-making, highlighting where to allocate resources and identifying which areas require the most focus for improvement. Through enhanced transparency, Evocon empowers organizations to chart a course based on their data insights. With over a decade of expertise in production monitoring, Evocon has been adopted in more than 50 countries and spans 14 diverse industries, all while offering support in 18 languages to cater to a global audience. This extensive reach underscores the platform's adaptability and effectiveness in various manufacturing environments.
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dbtdbt Labs is the leading analytics engineering platform for modern businesses. By combining the simplicity of SQL with the rigor of software development, dbt allows teams to: - Build, test, and document reliable data pipelines - Deploy transformations at scale with version control and CI/CD - Ensure data quality and governance across the business Trusted by thousands of companies worldwide, dbt Labs enables faster decision-making, reduces risk, and maximizes the value of your cloud data warehouse. If your organization depends on timely, accurate insights, dbt is the foundation for delivering them.
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DataBuckEnsuring the integrity of Big Data Quality is crucial for maintaining data that is secure, precise, and comprehensive. As data transitions across various IT infrastructures or is housed within Data Lakes, it faces significant challenges in reliability. The primary Big Data issues include: (i) Unidentified inaccuracies in the incoming data, (ii) the desynchronization of multiple data sources over time, (iii) unanticipated structural changes to data in downstream operations, and (iv) the complications arising from diverse IT platforms like Hadoop, Data Warehouses, and Cloud systems. When data shifts between these systems, such as moving from a Data Warehouse to a Hadoop ecosystem, NoSQL database, or Cloud services, it can encounter unforeseen problems. Additionally, data may fluctuate unexpectedly due to ineffective processes, haphazard data governance, poor storage solutions, and a lack of oversight regarding certain data sources, particularly those from external vendors. To address these challenges, DataBuck serves as an autonomous, self-learning validation and data matching tool specifically designed for Big Data Quality. By utilizing advanced algorithms, DataBuck enhances the verification process, ensuring a higher level of data trustworthiness and reliability throughout its lifecycle.
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Shoplogix Smart Factory PlatformGain immediate insights into the performance of your manufacturing floor with the Shoplogix smart factory platform, which empowers manufacturers to enhance overall equipment effectiveness, cut down operational expenses, and boost profitability. This platform enables real-time visualization, integration, and action on production and machine performance, making it a trusted ally for manufacturers aiming to enhance efficiency in their factories. By leveraging analytics and real-time visual data, you can gain crucial insights that facilitate well-informed decision-making. Uncover untapped potential on the shop floor to accelerate your time-to-value significantly. Through a commitment to education, training, and data-centric decisions, you can foster a culture of continuous improvement within your organization. Make the Shoplogix Smart Factory Platform the cornerstone of your digital transformation journey, allowing you to thrive in the competitive i4.0 landscape. Furthermore, streamline data collection and interoperability with various manufacturing technologies by connecting to any device or piece of equipment, ensuring a seamless flow of information. Automate the monitoring, reporting, and analysis of machine states to effortlessly track production in real-time, enhancing your operational capabilities even further. In doing so, you position your manufacturing processes for sustained growth and innovation.
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MaintainXMaintainX is a mobile-centric platform designed for work orders and procedures that empowers teams by clarifying their tasks and providing guidance on execution. Our service digitizes and streamlines various essential documents, such as: - Maintenance Work Orders - Safety Procedures - Environmental Checklists - Tooling & Gauge Reporting - Preventative Maintenance Procedures - Auditing/Inspection Workflows - Training Checklists By offering real-time insights from the field, we enable operational leaders to enhance efficiency and make informed decisions that drive productivity. This transformation not only simplifies workflows but also fosters a culture of safety and accountability within the organization.
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RaimaDBRaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
What is Lumada IIoT?
Design sensors specifically for IoT applications while improving the quality of collected data through the integration of environmental and control system information. This integration must happen in real-time alongside enterprise data, enabling the implementation of predictive algorithms that reveal new insights and maximize the value of your data for meaningful applications. Employ advanced analytics to predict maintenance needs, understand asset utilization, reduce defects, and optimize processes. Leverage the potential of interconnected devices to offer remote monitoring and diagnostic capabilities. Additionally, apply IoT analytics to foresee safety hazards and ensure regulatory compliance, which ultimately contributes to a reduction in workplace accidents. The Lumada Data Integration platform streamlines the rapid development and scaling of data pipelines, amalgamating information from a variety of sources, such as data lakes, warehouses, and devices, while proficiently managing data flows across different environments. By building partnerships with clients and industry stakeholders from diverse sectors, we can accelerate digital transformation, thereby creating new societal value. This collaborative method not only fosters innovation but also promotes sustainable growth in a world that is becoming increasingly interconnected, proving that teamwork is essential for success.
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.
Integrations Supported
AWS App Mesh
AWS IAM Identity Center
Hitachi Visualization Suite
Oracle Database@AWS
Integrations Supported
AWS App Mesh
AWS IAM Identity Center
Hitachi Visualization Suite
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
Hitachi
Company Location
Japan
Company Website
www.hitachi.com/products/it/lumada/global/en/about/index.html
Company Facts
Organization Name
Amazon Web Services
Date Founded
2006
Company Location
United States
Company Website
aws.amazon.com/iot-analytics/
Categories and Features
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
Field Service Management
Billing & Invoicing
Contact Database
Contract Management
Customer Database
Dispatch Management
Electronic Signature
Inventory Management
Mobile Access
Payment Collection in the Field
Quotes / Estimates
Routing
Scheduling
Service History Tracking
Time Clock
Work Order Management
Industrial IoT
Condition Monitoring
Data Visualization
Factory Data Analytics
Machine Learning
Machine Workflow Creation
Predictive Maintenance
Production Line / Factory Insights
Real-Time Monitoring
Reporting / Analytics
Smart Alerts / Notifications
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
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
Manufacturing Intelligence
Aggregation
Analysis
Contextualization
KPIs
Propagation
Visualization
Tradesman Job Management
Contract Management
Customer Database
Dispatch Management
For Builders
For Electricians
For Field Service Businesses
For HVAC
For Plumbers
For Roofers
Invoicing
Job Tracking
Payments
Quoting
Reporting
Scheduling
Time Tracking
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