AI-Driven Health Check for IBM Planning Analytics Applications

We have created a custom AI agent to perform a tailored health check of an IBM Planning Analytics Application. The agent leverages our MCP server and is able to navigate complex IBM PA environments. It performs an assessment of the environment, including memory consumption, performance and feeders and it issues a set of actionable recommendations.

Client Case Study

We have deployed the agent on an older IBM Planning Analytics model that ran into some memory and performance issues. This was a V11 IBM PA Application in the IBM Cloud. The system consisted of about 60 cubes, took up 820GB of memory with spikes to 1.2TB. The model was built ~10 years ago using a combination of external and internal resources and went through several updates and revisions over time.

The agent returned a concise 6-page summary with over 50 specific findings and recommendations. The highlights are as follows:

  • The agent summarized the largest cubes that consume the most memory

  • Identified 280GB (30%) in memory savings by optimizing feeders and stop overfeeding

  • Found 40+ broken references in rules and feeders

  • Pointed out that multi-threaded feeders and multi-threaded cube load are off, increasing startup time

  • Identified several areas where historical data could be archived and other cleanup and efficiency items.

The full 6-page sample report with detailed recommendations and findings can be downloaded using the form on the right.

Please contact us at solutions@acgi.com if you would like to discuss an AI-Driven Health Check for your IBM PA system.

Download Sample Report