Redlist is a reliability centered maintenance platform that extends traditional CMMS to track at the individual lubrication point, capturing execution data your ERP was never built to collect.
Available on web, iOS, and Android with full offline capability, Redlist replaces paper lube routes, eliminates pencil-whipping, and connects oil analysis data to technicians in the field.
Lubrication Management
Point-level route execution with the right lubricant, amount, and frequency per ICML standards.
CMMS and Asset Management
Component-level asset hierarchies, work orders, PM templates, and inventory. Integrates with SAP, Oracle EAM, JDE, and Maximo.
Operator Basic Care
Guided inspections and daily tasks that capture institutional knowledge before it retires.
AI Agents
Nine agents for FMEA, RCM, oil analysis, vibration & lubrication optimization.
Serving mining, oil and gas, chemical processing, food and beverage, packaging, and manufacturing. Deployed under 100 days.
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Interfacing’s Integrated Management System (IMS) is an AI-powered platform that unifies BPM, QMS, Document Control, and GRC into one platform. Organizations use IMS to model and automate processes, control documents, manage risks, and maintain regulatory compliance with full traceability and audit readiness.
Built for highly regulated sectors such as aerospace, life sciences, finance, and government, IMS provides real-time visibility, automated workflows, and AI-driven insights that improve quality and reduce operational risk. The platform is ISO 27001 certified and fully validated for 21 CFR Part 11, making it suitable for mission-critical environments requiring strong governance, security, and control. IMS also includes low-code automation, process mining, audit management, training tracking, CAPA workflows, and dashboards to help teams streamline operations and continuously improve. AI strengthens governance, improves accuracy, and reinforces regulatory control.
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RapidProM
Today's Information Systems (ISs) record huge amounts of data about the business processes they support. These data can be used for process mining. This way we can analyze the operational processes within an organization based on facts rather than fiction. Examples of these processes are the handling of a loan application within a bank or the treatment of a patient within a hospital. Currently, process mining is gaining more and more attention both in industry and practice. As such, the number of process mining tools is steadily increasing. However, none of these tools allow for composing and executing analysis workflows consisting of multiple process mining algorithms. As a result, the analyst needs to perform repetitive process mining tasks manually and scientic process experiments are extremely labor intensive. To this end, we have connected RapidMiner, which allows for the definition and execution of analysis workflows, with the process mining framework ProM 6.
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