Designates the starting point of the flow.

Designates the terminating point of the flow. More than one can be added.

Assigns values to variables or data structure elements.

Chooses between two flow branches based on the result of a condition check.

Directs the flow into one of multiple branches, each having its own condition check. The first branch with a satisfied condition is executed.

Loops over a collection of data elements and executes a sequence of flow steps for each element.

Invokes a built-in or user-defined function.

Invokes external services via HTTP REST call. Cookies and headers are fully supported.

Invokes external services via SOAP protocol. Cookies and headers are fully supported.

Executes a call to a relational database, such as PostgreSQL or MS SQL. Each DB connector step executes a preconfigured SQL query to retrieve or update persisted data.

Designates a starting point of a database transaction: a series of related database updates, all of which must either be successful or be completely undone in case of a failure.

Verifies and saves (commits) all database changes made in the flow since the execution of the “Begin Transaction” step.

Cancels (rolls back) all unsaved database changes that were made in the flow since the execution of the “Begin Transaction” step.

Executes various operations with blockchain smart contracts, such invoking their functions or checking their validity.

Retrieves information based on a selected function of the EVM Blockchain connector.

Raises an exception to indicate an abnormal situation in the flow. Multiple exception nodes can be added to the flow for different special conditions.

Executes an alternative flow to handle exceptional situations. Used together with a separate OUT node from which an abnormal result is returned.

Defines complex decision logic in a compact tabular format, with each table column representing a condition check or a decision parameter.

Defines a matrix with a set of structured ordered data records. It is used in scorecards and in workflows in general, e.g. as code lookup lists.

Calculates a predictive score that represents a likelihood of a future event based on input parameters (“characteristics”) and statistical correlations, typically extracted from the historical data.

Imports and executes various predictive analytic models (regressions, decision trees, etc.) generated by data science/machine learning tools in industry-standard PMML format.

Makes a call to another flow, returning the result of its execution. Allows to simplify complex decision logic by splitting it into a collection of smaller connected flows.