low code digital
Seamless integration of advanced signal processing with AI/ML capabilities, to create, deploy, and manage industrial digital twins
Industrial Digitization: Engineering, Analytics, and
An interactive digital twin platform that empowers users to swiftly craft analytical solutions to industrial problems from scratch and deploy them in real-time. With a drag-and-drop approach, Datacivet empowers even employees without experience in AI/ML can rapidly build highly accurate analytical models for complex industrial problems.
Comprehensive Signal Processing Suite
- Noise Reduction: Enhance data quality by eliminating sensor noise for critical input data.
- Filtering Techniques: Apply filters (high-pass, low-pass, median) to extract valuable signals from noisy data.
- Feature Extraction: Identify data stream features, aiding informed decisions.
- Data Fusion: Combine diverse data sources for a complete system view.
Real-Time Data Synchronization
Real-time data synchronization guarantees that your virtual models accurately represent the current state of your physical systems. This synchronization enables you to monitor, analyze, and optimize performance.
Datacivet offers a range of advanced visualisation features that allow you to:
- Monitor Real-Time Data: Visualize real-time data streams from your digital twin, providing insights into system behaviour and performance.
- Compare Data Streams: Overlay historical and real-time data for comparative analysis, identifying deviations and trends.
- Customisable Dashboards: Create interactive dashboards with various charts, graphs, and widgets, tailored to your specific needs.
Effortless Deployment and Integration
Deploy your digital twin to different environments, including cloud infrastructure, servers , and more. Datacivet offers integration with existing data sources, databases, and messaging frameworks, ensuring that the digital twins can analyze data from diverse sources.
Robust Validation and Testing
Datacivet provides robust validation and testing mechanisms, allowing users to simulate various scenarios and assess the performance of virtual models under different conditions. This iterative approach helps in fine-tuning the digital twins for optimal results.
Defining a Digital Twin using Datacivet
Import CSV, Excel, and DAT files, and interface with communication protocols like Modbus. Access cloud data securely via an integrated SSH client. Change the blank pages- add examples
Clean, filter, convert, blend, and alter your data with intuitive tools.
Develop classification and regression models using state-of-the-art algorithms. Datacivet supports various classification and regression algorithms like Catboost, XGBoost, Random Forest, Deep Learning and more. It can be divided into:
DataCivet incorporates an Auto Model feature that automates the pipeline creation process, optimizing hyperparameters using advanced techniques. It’s scalable, customizable and promotes transparency.
Load pre-trainined models effortlessly for real-time predictions