Secure your data in one click : automating redaction with Fast2 and AI

Compliance to laws about confidentiality and personal information is one of the hardest challenges we face in the 2020’s. Whether you want to restrict access to this data or build a non-prod environment as close as possible to the production environment, you cannot pay an army of reviewers to read all your documents and redact them one by one. By redaction, we mean here hiding -and ideally really removing- part of the information in the document content.

Let’s imagine we have a FlowerDocs production environment with a lot of documents randomly confidential or public (note that it is just an example and documents could be on any ECM environment as long as we have a connector for it in Fast2). We want to take those documents, redact the personal and confidential information, then push these documents into a similar non-prod environment.

That way, you end up with a clone-like environment, inducing the same constraints you will face during the production phase, minus the confidential aspect.

Fast2 handles bulk actions on these documents, and will provide all the tools you need for running such campaigns on a large load of artifacts. We’ll have extractors, injectors, queue-management, campaign scheduling, reports, etc.. Such a workflow in Fast2 would look a lot like this :

1. We extract the list of the documents with the FlowerSource
2. Then we extract the metadata and the content of those documents with the FlowerContentExtractor task
3. Then we intend to redact the sensitive documents (I’ll clarify this point later)
4. Finally, we either move the documents to a storage area with a MoveContent task, or we inject them into another FlowerDocs environment via the FlowerInjector task.

Note that we totally could add an AlterDocumentProperties task to change or encrypt the docu...

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