LotusEye offers AI-based anomaly detection that learns from normal sensor data and alerts on anomalies. Create models for free and upgrade if satisfied.
LotusEye offers AI-based anomaly detection that learns from normal sensor data and alerts on anomalies. Create models for free and upgrade if satisfied.
LotusEye provides an advanced AI anomaly detection system that automatically learns patterns from normal sensor data. Users can easily create their AI models by uploading data, with no prior AI knowledge required. The platform is free to try, and offers rich features like email notifications, data uploads via API, and multi-member management. Anomaly detection is simple and effective in three steps: upload training data, upload test data, and review the anomaly scores. Free model creation allows you to verify its effectiveness before committing to a paid plan.
Who will use LotusEye?
Industrial engineers
Maintenance teams
Data scientists
IoT developers
Manufacturing units
How to use the LotusEye?
Step1: Upload training data of normal operations to create an AI model
Step2: Upload test data to check for anomalies
Step3: Review the anomaly scores calculated by the AI
Platform
web
LotusEye's Core Features & Benefits
The Core Features of LotusEye
AI model creation from sensor data
Free model creation
Email notifications
API-based data uploads
Multi-member management
The Benefits of LotusEye
No AI expertise required
Free to start
Immediate anomaly alerts
Rich feature set
Scalable based on needs
LotusEye's Main Use Cases & Applications
Industrial equipment monitoring
Predictive maintenance
IoT device management
Environmental monitoring
Data-driven anomaly detection
FAQs of LotusEye
What types of sensor data can be used?
We support wide-format and long-format CSV files with appropriate headers. Detailed formats are provided on our website.
How can I upload sensor data?
Upload via the service interface or drag and drop CSV files. Higher plans support API-based uploads.
When does the anomaly score become high?
The score increases when test data deviates from the learned normal behavior. Model accuracy depends on training data.
How frequently is the anomaly score calculated?
The score is calculated hourly. For shorter intervals, data is averaged over each hour before scoring.
Can only sensor data be used for anomaly detection?
No, any numerical data in CSV format can be used. Examples include server logs and system command outputs.
What payment methods are available?
We support credit card payments through Stripe.
I want to know more about how to use the service.
Refer to our detailed user manual available on the website.
Why is there a free plan?
The free plan allows users to verify the effectiveness of the system before committing to a paid plan.
How do email notifications work?
Users receive email alerts when anomalies are detected based on the predefined thresholds.
Do I need AI knowledge to use the service?
No, the system is designed to be user-friendly and does not require AI expertise.