Complex File Transfer,
Run as One Automation.

File paths scattered across many locations, from factory equipment to research servers and branch storage, are grouped into a single Dataset and managed there. Instead of naming individual servers and directories again in every Flow, a Dataset composes the file group you need as the transfer target.

When a machine is added or a storage path changes, editing the Dataset applies it to every automation connected to it. Even with hundreds of machines and countless paths, the same automation structure holds without changing transfer settings one by one.

Search for a file and you can see which machine created it, which Dataset collected it, and through which Flow it was delivered where. Even when a file has passed through several servers and processing steps, every step’s run time and result is joined into one route.

Collection, transfer, processing, distribution and final storage: the whole journey of a file is traceable, which makes it easy to confirm the data arrived as it should. When something goes wrong you can see which step it stopped at and review the related transfer history.

A Flow can run at a set time or on a repeating cycle, on file creation and change events, or on an API request from an outside system. The next step proceeds on the completion and the result of the one before it, so collection, transfer, verification, distribution and follow-up work are connected automatically.

If a network failure interrupts a transfer, the data already finished is kept and the rest resumes from where it stopped; when only some files failed, only those files are processed again. Each step’s progress and result is visible, so even after a failure you can recover the work that needs it and manage whether the whole automation is complete.