Ventity’s modular model format allows for multiple people to work on different parts of a model at the same time. This video shows some of the opportunities for team model building in Ventity.
Need to see all the model year cohorts of diesel vehicles in your fleet? No problem. Ventity’s Entity Picker lets you select entities for viewing by model run, unique ID, or any entity attribute. Similarly, you can create collections of entities by attribute, and use those to compute aggregates – sum, average, maximum – for
This video demonstrates the use of entities to: represent markets with sparse offerings and new product introductions, create new structure on the fly, from data or random events model multiple scenarios simultaneously for an aggregate infection model, model the same infection process on an agent based social network, and calibrate a function to time series
Ventity can be used to put big data in context, by incorporating the learnings from big data in simulations that account for organizational structure and finances. Ventity can also do data intensive simulation, with an architecture friendly to relational data and dynamically changing lists, optimization for calibration, and much more on the road map.
You can pop up a chart on any variable in a diagram or list from a context menu. Charts feature smart scaling, brushing for values and legends, and drilldown, all a right-click away.
The Ventity equation editor, and other forms, are non-modal and use predictive typing. That makes it easy to navigate, view diagrams, and enter just what you need, without a complex dialog. Because a model has a limited set of terms, predictions are good, and model-diagram and units consistency checks further help to prevent errors.
Like Vensim®, which created the tool, Ventity has Causal Tracing for rapid model analysis:
In Ventity, you can introduce new entities on the fly during a simulation. You can introduce them via data, or programatically with discrete Actions. Introduce a firm into a market when you need it, or delete a cohort of products when they’re all sold. Simulate and review just your real behavior, without lots of clutter
Work efficiently with dockable windows and non-modal dialogs.
Ventity fits relational and ad hoc data sources naturally, because it represents detail with collections of entities rather than arrays. You can enter data easily, with convenient builtin tables or spreadsheet links. Collections are based on flexible lists of attributes; you can supply a table of entities without having to enumerate all possible combinations of