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A platform that puts the power of AI in your process team’s hands
The basetwo platform makes model-driven decision-making easy by allowing engineering teams to rapidly build, test, and operationalize digital twins of their plants that save time and manufacturing resources.
The basetwo platform makes model-driven decision-making easy by allowing engineering teams to rapidly build, test, and operationalize digital twins of their plants that save time and manufacturing resources.
Ingest
Integrate with both offline and online data sources
Build robust data pipelines with a drag and drop interface
Integrate process data from various data lakes
Clean
Gap fill and process data with signal smoothing and filtering
Visualize uploaded data in tabular spreadsheet views
Clean, filter, and transform data to prepare for analysis
Apply advanced signal processing techniques
Visualize
Overlap multiple time series datasets within a manufacturing line to visualize correlations and other process trends
Discover which variables contribute to process outputs using principal component analysis and other statistics
Build
Select from a library of industry-specific process models for each use case
Integrate process knowledge using drag-and-drop editor to customize the model
Any gaps in process knowledge are automatically filled by an ML model
Validate
Model predictions can easily be validated with domain knowledge of the process
Visualize model performance using a variety of robust metrics
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Deploy
Perform real-time virtual “what-if” experiments to predict process dynamics under novel conditions
Automatically determine process setpoints that maximize KPIs under various plant constraints
Integrate
Send digital twin KPIs to existing enterprise dashboards for visualization
Operationalize digital twin outcomes across your workforce with Office 365 notifications
Send work orders to existing maintenance management systems
Interested in learning more?
Unlock model-driven continuous improvement
Build from scratch or adapt from existing industry-tailored process models that allow your team to maximize the scientific and commercial value of your manufacturing data to improve product yield and quality.
Scale up and transfer your process with confidence
Leverage Basetwo’s physics informed machine-learning models with historical and parallel process knowledge to reduce uncertainty at different scales and process equipment.
Save time & resources with digital experiments
Fully-trained hybrid process models act as digital twins that capture underlying process dynamics, allowing for digital experimentation to test new operating ranges without consuming precious manufacturing resources.
Collaborate within and across departments
Integrate with multiple data sources to centralize knowledge and push model results to existing dashboards to easily visualize and collaborate on insights for scientists, engineers, and managers alike.
Work with models that learn as your team does
By leveraging machine-learning models, Basetwo ability to predict and understand your manufacturing processes improves as more data is gathered, improving return on investment over time.
Keep your process data secure, private, and encrypted at all times
The Basetwo platform is built on the most secure global cloud infrastructure, Amazon Web Services (AWS). Data is secured at rest and in transit with enterprise-level centralized logging, reporting, and analysis of all services and endpoints, giving you peace of mind.
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