This n8n workflow allows you to update user roles in Zammad based on data from an Excel file. The workflow automates role assignments, ensuring efficient and consistent updates. ## Features - **Excel Integration**: Impo
This AI agent reads an Excel file, matches users by email in Zammad, updates roles via the Zammad API, and logs outcomes for auditing. It continues processing even if individual updates fail, ensuring a reliable data-driven workflow. The end result is consistent access management across your help desk.
Performs structured, data-driven updates based on Excel data.
Reads the configured Excel file and validates required columns.
Finds Zammad users by email to ensure correct matches.
Updates user roles in Zammad via API with the specified roles.
Skips non-existent users or invalid rows without stopping the flow.
Logs successful updates and records errors for auditing.
Notifies or reports on failures based on configuration.
before → Pain points: 1) Manual Excel handling causes inconsistencies; 2) Updates are slow and error-prone; 3) No reliable audit trail for role changes; 4) Flows stop on first error and require manual intervention; 5) Lack of visibility into update outcomes. after → Outcomes: 1) Consistent, data-driven updates; 2) Faster, scalable updates from Excel; 3) Clear audit trails for every change; 4) Error-tolerant flow that continues on non-critical failures; 5) Actionable summaries for compliance.
A simple three-step flow that non-technical users can follow.
Fetches the Excel file from the configured URL, validates required columns (email, roles), and prepares rows for processing.
For each row, locate the user in Zammad by email and apply the specified roles via the API; skip non-existent users.
Record results, log any errors, and generate a summary report; continue on non-critical failures as configured.
A realistic scenario with concrete inputs and outcomes.
An administrator uploads an Excel file containing 15 emails and new roles. The AI agent processes the file in about two minutes, updates 12 users in Zammad, logs 3 failures with reasons, and outputs a summary report for auditing.
Roles that commonly manage access and user data across ticketing workflows.
Requires reliable, auditable bulk updates to user roles in Zammad.
Needs to apply onboarding/offboarding changes from HR spreadsheets.
Aligns access with employee data from Excel-based records.
Ensures role-based access controls are up to date across teams.
Consolidates data and ensures accuracy across systems.
Keeps support staff access aligned with org changes.
Core systems the AI agent interacts with to perform updates.
Authenticates with API key and locates users by email to update roles.
Provides emails and desired roles; data is read and validated before processing.
Common scenarios where this AI agent adds value.
Common questions about using this AI agent in your workflow.
The AI agent expects a source Excel file with at least email and desired role columns. It validates required columns before processing. If a row is missing data, it skips that row and logs the issue for later review. You can configure the data source URL and the columns used for matching and updates.
If a user cannot be found by email, the agent logs the failure and continues with the remaining rows. The workflow does not halt for missing users by default, unless you enable a hard stop in the settings. This prevents single errors from blocking updates for others.
Yes. The agent can map the Excel columns to the required fields and roles. If the column layouts change, update the mappings in the source configuration without altering the core logic. The validation step ensures required fields exist before attempting updates.
Updates are attempted individually for each row; on failure, the error is logged and processing continues if configured. A summary report is generated, showing successes and failures. You can adjust retry and continue-on-error behavior as needed.
Zammad API tokens are used for authentication. Tokens are provided as headers and kept separate from the data payload. Access control and scope are enforced by Zammad, ensuring only authorized updates are applied. You should rotate tokens regularly and monitor for any unauthorized access.
Yes. The AI agent is designed to be run on-demand or scheduled via your orchestration platform. Scheduling ensures regular updates without manual intervention. The run can be configured to skip non-critical errors while sending a summary afterward.
All processing results—successes and failures—are logged in a structured audit log and summarized in a report. Logs can be exported for compliance, and you can filter by date, user, or status. This makes reviewing updates straightforward during audits.
This n8n workflow allows you to update user roles in Zammad based on data from an Excel file. The workflow automates role assignments, ensuring efficient and consistent updates. ## Features - **Excel Integration**: Impo
