Rotomate

What Rotomate does

Rotomate provides an AI colleague for industrial condition monitoring that analyzes plant data, highlights issues, and recommends maintenance actions. It functions like a senior specialist, validating findings against machine context and maintenance history to deliver clear, prioritized maintenance decisions. The software aims to scale expert-level analysis across entire plants, addressing the bottleneck of expert attention in industrial reliability. It works with all sensors and data types, requires no new hardware, and is fast to deploy. Rotomate helps industrial reliability teams increase uptime, OEE, and production output by detecting developing issues early and focusing attention on assets that truly need it, reducing manual monitoring time and unnecessary inspections.

Products

• Rotomate's AI EngineerA virtual helper that reads machine signals, validates findings against machine context and maintenance history, and delivers clear, prioritized maintenance decisions. It interprets changes by combining signal data, machine context, and known failure patterns, providing full visibility into its reasoning.

Key capabilities

• Continuously analyzes plant data
• Highlights what needs attention
• Recommends maintenance actions
• No hardware lock-in
• Works with all sensors and data types
• Fast to deploy
• Applies human-like reasoning to every signal
• Interprets what a change actually means
• Combines signal data, machine context, and known failure patterns
• Provides prioritized insights on what needs attention, why, and what to do next
• State-of-the-art data visualizations and manual analysis tools for validation
• Full visibility into the reasoning behind every finding
• Structured analysis process for detected changes
• Identifies where the change occurred
• Selects relevant signals and views, analyzes trends and spectra
• Interprets findings in machine context
• Reasons if machine has something worth exploring
• Validates conclusions before reporting
• Simple, easy-to-use interface

Use cases

• Turning plant data into clear maintenance decisions
• Detecting developing issues early
• Focusing only on assets that actually need attention
• Reducing unnecessary inspections
• Scaling expert-level analysis without adding headcount
• Covering more assets with the same team
• Improving uptime and OEE for plant managers
• Providing a real-time view of what needs attention across the plant
• Retaining reliability knowledge within the system
• Reducing repetitive analysis work for reliability/vibration experts
• Focusing on high-impact diagnostics
• Scaling expertise across every asset
• Planning maintenance work weeks in advance for maintenance planners
• Understanding every finding without relying on experts
• Tracking all issues until resolved

AI approach

Rotomate uses AI to analyze industrial condition monitoring data, mimicking how experienced reliability engineers interpret machine signals, context, and maintenance history. It combines signal analysis, machine context, and human-like reasoning to identify issues, validate findings, and provide prioritized maintenance decisions. The AI is designed to be transparent, offering full visibility into its reasoning.

Tech named: AI, AI Engineer, machine data, diagnostic reasoning

Industries served

• Industrial
• Manufacturing

What it says sets it apart

• Goes beyond alerts to provide clear, prioritized maintenance decisions
• Acts as an AI colleague, mimicking a senior specialist's analysis
• Validates findings against machine context and maintenance history
• Addresses the bottleneck of expert attention in industrial reliability
• Scales expert-level analysis across entire plants without adding headcount
• No hardware lock-in; works with all sensors and data types
• Fast to deploy
• Applies human-like reasoning, not just anomaly detection or threshold-based alerts
• Provides full visibility into the reasoning behind AI findings, unlike black-box systems
• Combines signal analysis, machine context, and human-like reasoning
• Built by a team with deep mechanical engineering expertise and AI research focused on machine data and diagnostic reasoning
• Focuses on turning machine signals into explained analysis and maintenance actions

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.