IBM FileNet Content Manager
Overview
IBM FileNet Content Manager is a flexible, full-featured content management solution that provides the foundation for IBM Cloud Pak® for Business Automation. In labs you will get introduced to important core concepts of FileNet Content Platform Engine, Content Services GraphQL and IBM Content Navigator which will enable you to use FileNet Content Platform Engine to build the information architecture for automation projects realized with Cloud Pak for Business Automation.
The latest addition to the Content Services portfolio is IBM Content Assistant that provides natural language insights about business content in IBM FileNet Content Manager repositories. This is covered in the fourth lab.
Labs
Track 2 - Developer Role / Solution Implementation
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Setting up FileNet Content Manager for Automation Projects on Cloud Pak for Business Automation
In this lab, you will create a small hierarchy of Document classes to capture different kinds of documents together with custom metadata, and will learn about the most important security concepts. You will explore Document storage and learn to migrate documents between different Storage Areas. Further you will determine how to trigger custom actions for example when new documents have arrived, and how to configure and test functionality of content based retrieval, i.e. searches for documents based on information contained in the documents themselves, not (only) on their metadata.
In this lab, for triggering the custom actions, a custom JavaScript is used to file a newly uploaded document into a folder, those identity is derived from a search. The script is available in the Lab Data folder. Be aware that in the script, some replacements need to be made, to make it refer to the right properties. The username prefix is denoted by usrxxx in the script, and the xxx part needs to be updated.
Approximate Duration: 4 - 5 hours
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Interfacing FileNet Content Platform Engine with GraphQL on Cloud Pak for Business Automation
The second lab covering GraphQL builds on top of the first one, as the searches performed using GraphQL use the documents and document classes defined in the first lab.
Here you learn by a series of examples, how to build the most important queries using GraphQL. The examples also show how to download documents using GraphQL, how to create folders, and modify security settings.
Approximate Duration: 1.5 - 2 hours
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Introduction to Content Navigator in Cloud Pak for Business Automation
The third lab on IBM Content Navigator builds on top of the first, but not the second one. In it you can learn important concepts which allow you to configure IBM Content Navigator for a business application. The administration parts of the lab can only be performed in environments with administrative access. For other cases walkthroughs are provided in the lab guide.
This lab requires additional files that can be found in the Lab Data folder.
Approximate Duration: 1.5 - 2 hours
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The fourth lab demonstrates how IBM Content Assistant leverages Generative AI to extract information and insights from documents stored in an IBM FileNet Content Engine Object Store. It ensures secure access by restricting query results to documents the user is authorized to view.
The lab begins with an introduction to the IBM Content Assistant user interface, presented as an AI chat window in the lower-right corner of an IBM Content Navigator desktop. It also highlights the "Ask the Repository" feature, which enables users to query the AI across all documents in the FileNet repository, and the Document comparison feature.
The second part of the lab explores the underlying architecture. It explains the components of the IBM Content Assistant add-ons and how they enable integration with custom applications via the FileNet Content Engine API—such as the Client Onboarding Application.
The final section provides GraphQL example mutations and queries, which can be used as blueprints in such integrations.
Approximate Duration: 2 - 3 hours