Jungle AI is an AI-powered platform that uses historical data to monitor the health and performance of machines in various industries. Its advanced visualizations and tools allow users to explore developing issues to the sensor level, empowering them to find out exactly what is abnormal in their machines. Jungle AI's alarms are dynamic and contextual, and can detect abnormalities in any operation condition. The platform is built on top of advanced AI models that are agnostic to the application, making it suitable for different industries. Jungle AI is remotely deployed and offers a user-friendly interactivity based on the client's needs.
Jungle AI Features
- AI-powered Machine Monitoring: Jungle AI uses AI to learn from historical data and detect machine failures ahead of time, reducing downtime and increasing performance.
- Real-time Performance Tracking: Receive notifications of underperformance and investigate what to do about it.
- Collaboration: Resolve issues together and work in one place while looking at the same data from all possible angles.
- Remote Deployment: Jungle AI's technology doesn't require any hardware installation, allowing for fast product deployment.
- Unsupervised Learning: Jungle's machine learning models are trained without labeled data, allowing for more flexibility.
- Contextual Alarms: Jungle's alarms are dynamic and contextual, detecting abnormalities in any operation condition.
- Industry Agnostic: Jungle's advanced AI models are built to fit different industries, including manufacturing, solar, and wind.
- User-Friendly Interactivity: Jungle AI offers a user-friendly interactivity based on the client's needs.
- Built on Customer Feedback: Jungle is built on intensive customer feedback, creating a highly collaborative case environment.
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