Volupe Group przejęła od Endego działalność związaną ze sprzedażą i dystrybucją oprogramowania Siemens i Altair.
Endego koncentruje się na dalszym rozwoju usług inżynieryjnych i digitalizacyjnych. Dowiedz się więcej
Siemens’ Rapidminer portfolio supports data preparation, analytics and machine learning. It includes tools for working with data, building models and visualizing results. Choose applications according to the data sources, team requirements and deployment approach.
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Rapidminer AI Studio enables teams to build AI and machine learning models using visual workflows and Python or R code. Rapidminer AI Hub and AI Cloud support model sharing and deployment. Integration, access management and deployment options depend on the products and configuration used.
Rapidminer SLC runs SAS language programs and combines them with Python, R and SQL. It helps organizations reuse existing code in a modernized analytics environment. Check library, procedure and data-connection compatibility for the specific program and software version.
Rapidminer Monarch extracts, prepares and transforms data from sources including PDF reports, spreadsheets and text files. Visual no-code tools help create repeatable data preparation workflows. Automation and deployment capabilities depend on the selected application, including Rapidminer Monarch Server.
Rapidminer AI Studio supports data preparation, machine learning model building and evaluation, including AutoML workflows. Visual processes can incorporate Python or R components. Assess model quality using appropriate test data before using predictions to inform decisions.
Rapidminer Panopticon supports data visualization and streaming analytics. Interactive dashboards help analyze live and historical data, identify trends and explore anomalies. Data availability and display latency depend on the source, connection and system configuration.
Simcenter PhysicsAI learns from previous simulation results to predict the behavior of new geometries. It helps engineers compare design alternatives quickly. Assess prediction quality and validate results, particularly outside the training distribution; AI complements traditional solvers.
