AI Workflows Automation #4965: NPS Collection with OpenAI + Slack + Raycast

Problem

AI-assisted nps collection needs guardrailed hand-offs from OpenAI to Slack so humans can review edge cases.

This pattern separates inference, routing, and downstream action.

Workflow

Event in OpenAI → validate payload → update Slack → log outcome for review.

Tools Used

• OpenAI
• Slack
• Raycast

Setup Steps

1. Create credentials for OpenAI, Slack, Raycast in your orchestration platform.
2. Define the nps collection trigger in OpenAI.
3. Map required fields from OpenAI to Slack.
4. Add error handling appropriate for a Easy workflow.
5. Run a test payload, then enable production execution (~45 min typical setup in our dataset).

Expected Outcome

• A repeatable nps collection path for ai workflows teams.
• Less context switching between OpenAI and Slack.
• Easier hand-offs for the next ops owner.

Benefits & ROI

• Library metadata: Medium ROI tier · Easy difficulty · ~45 min setup estimate.
• Reduces manual nps collection steps between OpenAI, Slack, Raycast.
• Provides a baseline you can extend with approvals, logging, or QA gates.

Troubleshooting

• Inspect execution logs for HTTP 429 rate-limit responses.
• Run a single test record before bulk backfill.
• Pause the workflow before rotating API keys, then resume after credentials update.