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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Denodo is an intelligent data platform that helps organizations deliver live, unified, and governed data for trustworthy AI, analytics, and self-service initiatives. The platform uses logical data management to connect distributed data across hybrid, multi-cloud, on-premises, SaaS, and third-party environments without requiring data movement or duplication. Denodo helps businesses integrate data silos, enable self-service access, enforce governance, deliver real-time insights, and enrich data with business context. It is designed to support agentic AI by giving AI agents accurate, up-to-date, and governed enterprise data for better decisions and actions. The platform includes capabilities such as zero-copy data access, unified semantics, centralized compliance, natural language search, data marketplaces, and optimized query performance.
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AWS IoT Analytics
IoT data is highly unstructured which makes it difficult to analyze with traditional analytics and business intelligence tools that are designed to process structured data. IoT data comes from devices that often record fairly noisy processes (such as temperature, motion, or sound). The data from these devices can frequently have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of additional, third party data inputs. For example, to help farmers determine when to water their crops, vineyard irrigation systems often enrich moisture sensor data with rainfall data from the vineyard, allowing for more efficient water usage while maximizing harvest yield. AWS IoT Analytics automates each of the difficult steps that are required to analyze data from IoT devices. AWS IoT Analytics is a fully managed and pay-as-you-go service that scales automatically.
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