Compare Lumada IIoT vs. Oracle IoT Intelligent Applications Cloud

Tractian is the Industrial Copilot for maintenance and reliability, combining hardware and software solutions to monitor asset performance, manage industrial operations, and implement predictive maintenance strategies. Its AI-driven platform empowers businesses to prevent unplanned equipment downtime and boost production output. The company is headquartered in Atlanta, GA, and extends its presence globally with offices in Mexico City and Sao Paulo. Learn more at tractian.com.

The Asset Guardian (TAG) Mobi: Tackle Downtime with TAG Mobi TAG Mobi is a fully embedded preventive maintenance and asset management (EAM) solution within Microsoft Dynamics 365 Business Central. Designed for modern manufacturing and infrastructure operations, TAG Mobi helps reduce risk, minimize downtime, and streamline maintenance workflows—all from within your existing Business Central environment. From proactive asset health monitoring and predictive maintenance to real-time mobility and AI-powered adoption tools, TAG Mobi equips maintenance teams with everything they need to boost performance and take control of asset operations. Key Features: • Fully embedded in Microsoft Dynamics 365 Business Central • Real-time mobile access for on-the-go asset tracking • Predictive maintenance to reduce unplanned downtime • AI-assisted onboarding for faster adoption • Advanced APM tools to monitor asset health and anticipate failures No silos. No extra software. Just a seamless, native experience that empowers maintenance teams and provides managers with the insights they need—right inside Business Central.

Epicor Connected Process Control provides a simple-to-use software solution that allows you to configure digital work instructions and enforce process control. It also ensures that operations are error-proof. Connect IoT devices to collect 100% time studies and process data, images and images at the task level. Real-time visibility and quality control on a new level! eFlex can handle any number of product variations or thousands of parts, whether you are a component-based or model-based manufacturer. Work instructions can be linked to Bill of Materials, ensuring that products are built correctly every time, even if changes are made during the process. Work instructions that are part a system that is advanced will automatically react to model and component variations and only display the right work instructions for what's currently being built at station.

For over two decades, Shoplogix has helped leading manufacturers worldwide unlock hidden production potential by transforming real-time machine and performance data into actionable insights. The platform automatically captures signals like downtime, scrap, and throughput, delivering visual dashboards that enable teams to identify bottlenecks, reduce losses, and improve continuously—both during shifts and in post-shift analysis. With OneSignal connectivity, Shoplogix integrates with any machine brand or type to deliver real-time, granular insights on slow-running, starved, or idle machines. Its intuitive visual management system allows operators and managers alike to quickly detect and act on issues. Integrated analytics provide powerful, slice-and-dice capabilities similar to leading BI tools, without leaving the platform. Designed for agility, Shoplogix supports scaling from a single line to multi-plant operations across geographies. Continuous improvement tools like Action Plans and Digital Andon alerts keep teams engaged, aligned, and empowered to act—making Shoplogix a powerful ally in the pursuit of operational excellence.

eMaint, a cloud-based Computerized Maintenance Management System (CMMS), is an award-winning software that helps organizations improve their ability to manage their maintenance reliability operations, equipment, and compliance. eMaint is suitable for any size company or enterprise. It integrates all the tools they require into one powerful platform, saving companies valuable time and money. It includes maintenance scheduling, work order management, reports and dashboards as well as predictive maintenance, preventive maintenance and mobile maintenance. It also manages inventory management and asset management.

Evocon is a cloud-based production monitoring solution that helps manufacturing companies manage and improve their production efficiency. Evocon automates and digitizes the collection of data from production machines. We then transfer the collected data to the cloud so that manufacturers can access it in real-time, either on-site or remotely. Finally, by visualizing the data in an intuitive way, we make it actionable. This enables manufacturers to track their downtime, reduce costs and optimize the use of their production equipment. It also gives them a platform for smart decision-making – where to invest and what areas need the most attention. By providing transparency, we help companies find a way forward based on what their data says. More than 10 years of experience in production monitoring Used in 50+ countries Covering 14 different industries Available in 18 languages

MaintainX is a mobile-first work order and procedure platform that allows teams to know what they need to do and how to do it. Here's what we digitize and take away from the clipboard: -Maintenance Work Orders -Safety Procedures -Environmental Checklists -Tooling & Gauge Reporting -Preventative Maintenance Procedures -Auditing/Inspection Workflows -Training Checklists We help operational leaders become more efficient by delivering real-time business insights from the field.

The HiveMQ Platform provides a scalable, reliable data backbone with an event-driven MQTT architecture. Here are a few highlights: 1. MQTT Broker: At the heart of the HiveMQ platform is a fully MQTT-compliant broker purpose-built for fast, reliable, bi-directional data movement between IoT devices and enterprise systems. 2. Edge Data Integration: HiveMQ Edge seamlessly integrates edge data by converting industrial protocols into standardized MQTT, enabling an interoperable IIoT infrastructure. 3. IoT Streaming Governance: Data Hub transforms data in flight, passing only the most relevant, contextualized data to cloud and enterprise systems. 4. UNS & IT/OT convergence Enabler: Commonly used as the backbone for Unified Namespace architectures and seamlessly connects OT devices with IT systems for full visibility and interoperability. 5. Distributed Data Intelligence: HiveMQ Pulse unifies and contextualizes data across the enterprise for smarter decisions exactly where they matter most. 6. Maximum Interoperability: Runs anywhere on-premises or in public or private clouds. Efficiently connects to streaming applications, databases and data lakes with a Java SDK to build your own 7. Scalability to Support Growth: Elastic scaling with automatic data balancing and smart message distribution. Proven benchmark of up to 200M active clients with 1.8B messages/hour 8. Business Critical Reliability: Zero message loss with persistence to disk and offline queuing. No single point of failure due to masterless cluster architecture and zero downtime upgrades

dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use. With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.