AI That Understands Your Data, Trains the Model and Takes Action. Powered by Agent AI
Predictor analyzes your raw data using a dedicated AI agent, cleans and prepares it, and generates new features — selecting the most statistically correlated and informative ones through an autonomous feature selection agent.
It then trains machine learning models tailored to your goals, and with one click, deploys them to your edge environment.
Once deployed, Predictor acts as a live agent: detecting anomalies, forecasting outcomes, and taking intelligent actions in real time.
This multi-agent AI system integrates seamlessly with your OT and IT infrastructure, transforming your operations into a self-operating, AI-driven environment.
Anomaly Detection
Predictive Maintenance
Predictive Quality
Business Process
Demand Forecasting
Energy Consumption
Order Management
Production Planning
Process Optimization
Analysis
Advanced Dashboard
Analysis Tools
HOW IT WORKS?
Here’s how Predictor works, step by step
1
Data Upload
2
Pre-Processing
Manual or AI Agent
3
Feature Selection
& Generation
Manual or AI Agent
4
AI Model Training
Manual or AI Agent
5
Deployment
Manual or AI Agent
6
Real-Time Monitoring
& Autonomous Action
Why it matters?
Whether you're uploading a CSV file or streaming from OT/IT/Cloud systems, clean and well-structured data is the foundation of reliable predictive models.
Clean, Structured Data for Machine Learning
Predictor ingests raw data from multiple sources, including sensors, PLCs, CSV files, databases, data lakes, data warehouses, and external APIs. A dedicated preprocessing agent automatically cleans, normalizes, and aligns the data: filling missing values, correcting time drifts, removing outliers, and structuring it for machine learning.
Why it matters?
Selecting and generating the right features improves model accuracy, prevents overfitting, accelerates training, and enhances explainability, especially in complex industrial systems.
Discover What Matters — and Create What’s Missing
The Feature Selection Agent analyzes the cleaned dataset to identify the most predictive variables. It uses statistical correlation, domain relevance, and pattern recognition to filter out irrelevant or redundant inputs.
But it doesn’t stop there — the agent also generates new synthetic features by combining, transforming, or aggregating existing variables to uncover deeper insights.Why it matters?
Generic models often miss the nuances of industrial data. Purpose-built ML delivers higher accuracy, faster inference, and more substantial alignment with real-world KPIs.
Train Purpose-Built Machine Learning Models, Automatically
The Modeling Agent trains AI models that are tailored to your specific operational goals — whether you're forecasting energy consumption, predicting equipment failure, or optimizing cycle time.
It automatically selects the best method (regression, classification, clustering, forecasting) and model (RNNs, Transformers, CNNs, Traditional ML), tunes hyperparameters, and validates performance through cross-validation.
Why it matters?
Cloud-based predictions are often too slow or unreliable for industrial use. Edge deployment delivers low-latency, high-availability AI where your operations happen.
Deploy Machine Learning Models to Edge Devices in One Click
Once a model is trained, the Deployment Agent automatically converts it into an optimized runtime format compatible with your edge environment. With a single click, you can deploy the model to industrial PCs, IoT gateways, or other edge AI hardware — without writing any code.
Predictor ensures seamless communication with your on-site infrastructure, enabling real-time inference directly within your factory floor.
Why it matters?
Real-time response prevents damage, reduces downtime, and improves process stability — all without human intervention.
Monitor, Decide, and Act — in Real Time.
Once deployed, Predictor continuously monitors your production data, detects anomalies, and takes autonomous action when needed, without requiring manual intervention.
What it Does?
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Continuously analyzes live operational signals (temperature, energy, vibration, etc.)
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Identifies deviations and predicts potential failures
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Sends real-time alerts via:
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Email
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Dashboards
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OT protocols (Modbus, MQTT, OPC-UA)
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Executes rule-based or ML-driven actions:
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Stops or pauses machines
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Activates backup or cooling systems
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Adjusts production flow
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Sends instructions to PLCs or edge controllers
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USER INTERFACE
EVERYTHING YOU NEED
All the Essential Tools for Analytics & Prediction
Dashboard
Predictor's dashboard provides an intuitive, real-time overview of your data and analytics. Visualize key metrics and insights at a glance, detect anomalies, and track demand forecasts. The customizable interface ensures you have all the critical information you need at your fingertips.
Built-in IoT Device Connectors
Predictor can communicate with devices that use Siemens S7, Modbus TCP, and MQTT protocols.
Data Preparation & Analysis Tool
Prepare and quickly analyze your data on the Data Preparation & Analysis Page. Clean, enrich, and optimize your datasets to ensure the highest accuracy for your AI models. Utilize advanced analytics tools to uncover patterns and trends and transform raw data into actionable insights.
Built-in IT System Connectors
Predictor can quickly and easily integrate with ERP, MES, QMS, and similar IT systems.
Training & Testing Tool
The Training & Testing Tool in Predictor allows you to build, train, and test AI models with No-Code. Use the test phase to set parameters, test trained models, and validate model performance. Ensure your models are accurate and reliable before deployment.
Deployment Tool
Deploy trained models quickly and easily. Transfer AI models to your production environment with a single click and start using them immediately.
FEATURES & DETAILS
YOUR SMART ASSISTANT