In4act team applies analytic techniques to business problems such as statistical, machine learning and deep learning algorithms for classification, continuous estimation, clustering, anomaly detection, and producing recommendations.
As part of Kaunas University of Technology, the In4act team collaborates with business companies regarding:
– Conducting R&D activities as partners in EU funds’, MITA, LMT funded projects
– Directly providing services for companies
– Automated recommendations for forms’ fields auto-complete
– Automated recommendation for task assignments
– Prediction of task accomplishment duration
– Company-specific ERP-embedded recommendations
– Order-to-cash, Purchase-to-pay, Manufacturing-to-release process discovery, conformance checking and improvement insights (e.g., long cases, bottlenecks, over-exploited resources)
– Order-to-cash, Purchase-to-pay, Manufacturing-to-release process real-time case prediction based on historical data
– Company-specific use cases of process mining
– Employee productivity and health improvement insights
– Customer habits insights
– Process improvement insights
– Company-specific use cases of wearables-based data collection and analytics
– Sales and demand forecasting
– Predictive maintenance
– Yield optimization
– Procurement and spend analytics
– Inventory and parts optimization
– Statistical process control
– Company-specific use cases of analytics for manufacturing and supply chain
– High quality and transparent data flows to monitor progress with respect to supply chain goals.
– Data hub for circular economy monitoring and reporting connected to circular economy data and software.
– FAIR principles
– Machine-actionability of data collection
– Analytics on custom business use cases
