Setting Up an Incoming Webhook Step in Streamline

The incoming webhook step lets you trigger a Streamline workflow using an HTTP GET or POST request from any external system—such as Salesforce, ticketing platforms, or automation tools. When the incoming webhook fires, it can pass payload data (like a customer ID or customer name), which Streamline automatically extracts and makes available for use throughout the workflow.

To make setup simple, the incoming webhook step includes a built-in listening mode. This allows you to send sample payloads while configuring the step. Streamline’s AI will parse the incoming data, suggest field mappings, and let you adjust labels and data types as needed.

🔒 Privacy Note: Streamline AI does not use your customer data for training. All parsing and field suggestions are scoped to your workflow only.

What It Is (and Why It Matters)

The incoming webhook step makes it easy to connect external systems to Streamline without coding custom integrations. It:

• Accepts incoming HTTP POST and GET requests
• Parses incoming data into usable fields across the workflow
• Returns session URLs for workflows with customer-facing steps

This means you can start workflows in Streamline directly from the tools your teams already use—like CRMs, ticketing systems, or automation platforms.

What You Can Do with the incoming webhook Step

The incoming webhook step enables you to:

• Trigger workflows from external systems using GET or POST requests, sending in contextual details like a customer ID or order number.
• Parse and reuse incoming data throughout the workflow—for searching datasets, prefilling forms, or personalizing notifications.
• Quickly configure field mapping with AI-suggested names and types (which you can adjust manually).
• Test and refine your setup using a dedicated Test URL before switching to Production.
• Relisten mode will not break any steps that are already using the old fields. In-use fields keep their existing labels, while new fields from the updated payload are added alongside them.
• Provide session URLs to end-users when workflows include customer-facing steps.

Limitations

• Must be the first step in the workflow
• Only one incoming webhook entry point is supported per workflow
• Private (authenticated) incoming webhooks are not yet supported
• Relies on test payloads for schema definition (no visual schema editor)
• Supports only query string and JSON payloads (multipart forms not supported yet)
• If no customer-facing steps exist, no session URL will be returned

How to Set Up an incoming webhook Step

1. Add the incoming webhook Step

• In the workflow builder, select incoming webhook as the first step.

• You can rename the step or keep the default name. Click the step to make edits.

⚠️ Note: As a reminder, the incoming webhook step must always be the first step in your workflow.

2. Copy the incoming webhook URL

• On the configuration screen, you’ll see the incoming webhook URL.
• This is the custom URL you’ll use to connect your external application.
• Use the toggle to switch between Test and Live modes.

3. Set the HTTP Method

• Under the General tab, the default method is POST.
• You can switch to GET if needed.

4. Send a Test Payload

• Copy the Test URL (provided when the step is in listening mode).
• Send a sample payload using a tool such as Postman.

5. Review and Map Fields

• Streamline AI will parse the incoming payload and suggest field names, types, and labels.
• You can edit these suggestions or add custom labels as needed.
• By default, the payload is hidden, but you can expand it at any time to review details.
• Use Re-extract to send new payloads and update field mapping as your schema evolves.

6. Save Your Configuration

• When ready for production, switch to the Live URL to trigger real sessions.
• Ensure payloads sent to Prod match the expected schema.
• Once you’re satisfied with the setup, click X to close the step and save your changes

Summary

The incoming webhook step is a powerful entry point for automating workflows from external systems. By sending contextual data at the start of a workflow, you can:

• Kick off Streamline processes from your core tools
• Ensure workflows have the right data from the start
• Build seamless, automated integrations without writing code