We need to discuss some basic concepts to better grasp Rindap’s take on workflow automation.
Everything starts once the workflow has been created on the modeller. Workflow is a diagram of your business processes. Above all, it is the way how your operations work. It can be as simple as the arrangement of a service appointment or as complex as the production planning of an electronics factory that also needs to have its production equipment’s condition checked via IoT. Creating the diagram on the drag & drop modeller is the first step for workflow automation in Rindap approach.
Setting the workflow
The workflow is built to get tasks done. Workflows start with tasks. Tasks mean data that are generated once triggered by a system that interacts with Rindap. For instance, consider Rindap is automating the loan application assessment process of a creditor. The workflow should start with the generation of a task. The task in this scenario can be a loan application in the creditor’s server. Tasks contain data. In this case, data can include the applicant’s name, address, identification and so on. Once generated, Rindap’s RESTful API. inserts the task to the designed workflow.
Filters act as the decision points in your workflow. In addition, filters have a logic-based structure. They keep the business rules and the parameters to analyze the data in the tasks and channel tasks according to the workflow.
Queues are the elements that tasks are directed to be assigned to the available and appropriate worker.
Workers can be anything that operates to complete a task. It can be an email reports service that checks the email is, it can be a CRM application that opens a new opportunity record or it can be the restaurant waiter that inserts orders to the software through a smartphone. It can even be a smart production robot that runs on IoT.
Continuous automation with the tasks’ update
The main flexibility with Rindap is that the workflow does not end with the matching of a task to a worker. The process continues by adding more filters subsequently. So once a worker performs its duty, the response updates the task’s initial data.
The task with updated data continues to the following filters for assessment and assignment. This goes perpetually without any limitation as per requirements designed on the workflow. If you would like to read about a hypothetical example of a Rindap use case and get to learn more details please take a look at this article.