Woost uses process mining techniques to discover new processes. Data generated by the execution of processes, e.g. in multiple Kanban boards, is aggregated and analyzed. Thus new and more effective processes are discovered.
Modeled processes are analyzed and compared to the real data generated by users during process execution. With this information, Woost continuously supports users in improving their processes.
In most companies, different teams observe similar problems. It is not uncommon for different development teams to solve the same problem. Woost detects such redundant developments and encourages a collaborative and transparent solution.
Using hierarchical models, Woost is able to aggregate information across multiple levels. Data from chats, Kanban cards and other views is combined to summarize information and highlight current topics in teams or departments.
Finding the right category or tag is hard. Woost combines semantically identical tags, so you don't have to worry about finding the best fitting tag.
Woost informs users about features when they are needed. In addition to the process optimization features, users are informed about how they can improve (personal) workflows with advanced features in Woost.