Any idea —- How can an AI‑driven monitoring layer be built for Anaplan integrations to analyze logs, schedules, and execution results, and generate contextual alerts for support teams when failures occur ?
To build an AI-driven monitoring layer for Anaplan, you first need to centralize metadata by using Anaplan APIs or the CloudWorks service to export audit logs, task history, and integration results into a data lake (like Snowflake or Azure Data Lake). Once centralized, you apply Anomaly Detection models (such as Isolation Forests or LSTM networks) to establish a baseline for normal execution times and data volumes, allowing the system to flag "silent failures"—like a successful EmpowerRetirement com run that processed zero records—which traditional rules often miss. These insights are then fed into a Generative AI agent that correlates the error codes with historical resolution data to generate contextual alerts (e.g., "Failure due to locked workspace; notify Admin A") sent directly to Slack, Teams, or ServiceNow.
Hello, I have a use case where a user will create a child if they want to make adjustments to an initial value entered at the parent level. The reason the "parent" list may not have children is that not all the list members will have adjustments. The users want to see all L1 items on the same grid as L1 items with L2 items…
We have a question regarding the behavior of the XL3dowriteback formula. Our understanding is that this formula allows writeback to be controlled on a cell-by-cell basis. In our operation, when we need to clear a previously written-back value due to an input error or similar reason, we do so by entering 0. However, when…
We added new bed types to eventually move from the old "All Beds, single, double" I inputted the data into the new bed types Went to double check flow into other modules and found that they are being double counted even though I blanked the original columns out. I am not sure why it is still counting All Beds even if it is…
