Interfacing’s Integrated Management System (IMS ) is an AI-supported platform that brings BPM, QMS, Document Control, and GRC together in one environment. Teams use IMS to design and manage processes, govern documentation, oversee risks, and demonstrate compliance with complete visibility and reliable audit evidence.
Built for sectors that depend on strict oversight, such as aerospace, life sciences, public sector, and financial services, IMS offers real-time monitoring, automated workflows, and AI-driven analytics that strengthen quality and lower operational exposure. The system is ISO 27001 certified and validated for 21 CFR Part 11, ensuring secure and compliant use in regulated operations. IMS also provides low-code automation, process mining, audit tools, training management, CAPA workflows, and dashboards that help organizations improve performance and maintain regulatory control. AI enhances governance, improves precision, and supports continuous compliance.
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Redlist is a reliability centered maintenance platform built for industrial teams that need more from their CMMS. Where traditional maintenance software stops at the work order, Redlist continues to the shop floor, tracking every lubrication point, inspection task, and operator action.
The platform runs on web, iOS, and Android with full offline functionality, purpose-built for technicians in plants, mines, and refineries where connectivity is unreliable.
Lubrication Management
Redlist manages lubrication at the individual point level, assigning the correct lubricant, volume, and frequency to every grease fitting, oil drain, and sample port. Routes are executed digitally, replacing paper-based systems and eliminating the pencil-whipping that hides missed tasks. Oil analysis results from labs integrate directly so technicians see condition data alongside their route.
CMMS and Asset Management
Manage assets from the enterprise level down to individual components. Create work orders, build PM templates, track parts inventory, and schedule predictive maintenance. Connects to existing ERP and CMMS systems including SAP, Oracle EAM, JDE, and Maximo, bridging the gap between enterprise software and field execution.
Operator Basic Care
Enable frontline operators to perform guided daily inspections and basic maintenance tasks, building a digital record of institutional knowledge that would otherwise be lost when experienced technicians retire.
AI Agents
Nine purpose-built agents for FMEA analysis, RCM-based PM development, oil analysis interpretation, vibration diagnostics, and lubrication optimization.
Serving mining, oil and gas, chemical processing, food and beverage, packaging, paper and corrugated, and manufacturing. Deployed under 100 days.
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IBM Process Mining
IBM Process Mining allows organizations to identify business processes that could benefit the most from automation. It uses business system data to create an end-to-end process and visualize any bottlenecks or derivations that may be hidden in business processes.
IBM Process Mining gives users an objective view of business processes and identifies areas where automation initiatives should be focused. It also allows users to create what-if scenarios to prioritize automation projects.
IBM Process Mining is a foundational capability for IBM Cloud Paks for Automation. It finds the best process candidates for automation and calculates expected ROI. It also shows the impact of automation initiatives throughout the process before implementation.
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RapidProM
Modern Information Systems (ISs) accumulate vast quantities of data regarding the business processes they facilitate. This data serves as a foundation for process mining, enabling organizations to scrutinize their operational processes based on empirical evidence rather than assumptions. For instance, this can involve analyzing the workflow of a loan application at a bank or evaluating the patient care procedures in a hospital. Currently, there is a growing interest in process mining within both industry and academic settings. Consequently, the availability of various process mining tools is on the rise. Despite this growth, existing tools do not support the creation and execution of comprehensive analysis workflows that utilize multiple process mining algorithms. This limitation forces analysts to repetitively conduct process mining tasks by hand, making scientific experimentation in this area labor-intensive. To address this challenge, we have integrated RapidMiner, a platform that enables the design and execution of analysis workflows, with the ProM 6 process mining framework, thereby enhancing efficiency and effectiveness in process mining endeavors. This integration aims to streamline the analysis process, ultimately improving productivity for analysts in the field.
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