Flowable blog

Optimizing end-to-end business automation can be a tall task for legacy systems that lack integration abilities such as APIs. But robotic process automation can provide a successful interim transition to replacing these when time to market is crucial.

Enterprises need to process a large volume if documents daily — quickly and accurately. Flowable uses Intelligent Document Processing (IDP) to improve content processing and support enterprises in managing documents end-to-end.

CMMN was mainly designed with case management in mind to handle dynamic, human-driven processes, where the execution is not always a straight line, but might involve human decision to drive the process forward. But it can do way more than that.

Tools like ChatGPT can handle a variety of business tasks, automating nearly everything. And it’s true, GenAI really can do a wide range of tasks that humans do currently. Why not let business users work directly with AI then? And what about Agentic AI?

In the past few months, this has culminated into a clear understanding of the strengths and weaknesses of the Generative AI (GenAI) technology; and where it makes sense to integrate with it and – perhaps more important – where it doesn’t make sense.

As AI gains prominence as a pivotal technology and enterprises increasingly seek to leverage its capabilities, we are actively exploring diverse avenues for integrating AI into process automation.

The key to managing complexity is to combine different and multiple tools leads to better, faster, and more maintainable solutions. For example, combining BPMN with CMMN.

Discover the reasons behind our brand-new Flowable eLearning platform and explore its features by registering for our inaugural free course.

Data is a crucial part of modeling and executing cases and processes. Our new module, Data Dictionary, empowers modelers to define which data structures and constraints are needed in the case or process model and all its child models.