Agentic Generative Journey

From start to finish, set up a flow using Generative Journey in agentic mode with NLX

What's Generative Journey in agentic mode?

The Generative Journey node is a powerful building block in your flow that brings a large language model (LLMs) into the process. When set to agentic mode, the node can call on a range of tools you assign to it, such as managed or custom data requests, modalities, knowledge bases, or even other flows. It knows when and how to use these tools to facilitate a task while conversing with a user, and can naturally collect details from the user, like name, order number, or t-shirt size without requiring a rigid, pre-mapped flow.

Imagine a customer uses your conversational app and says: "I’d like to exchange my shirt for a larger size."

With agentic Generative Journey:

  • A flow is invoked that is designed to handle an order return

  • When the Generative Journey node is hit, the agent powering it understands the intent (exchange request) and gathers needed details like order number, shirt size, and preferred shipping option directly from the user in natural conversation

  • It then calls a custom data request to retrieve the order from your backend system

  • If available, it uses a modality (like a carousel of available sizes/colors) to let the customer pick a replacement

  • It may reference a knowledge base for return policies and automatically share that information with the customer

  • Finally, it executes the exchange by triggering another flow or integration

In practice, this one node can replace dozens of traditional workflow nodes, giving you far more flexibility and making your flows cleaner, smarter, and easier to maintain.

Checklist

You'll complete the following to successfully launch a workflow powered by Generative Journey in agentic mode:

Step 1: Set up tools

Est. time to complete: ~10 minutes

Tools are the building blocks the agent can call on to complete tasks. These include:

  • Data requests (custom or managed integrations): Retrieves or sends information from APIs or integrations

  • Modalities: Presents information in different formats (e.g., a carousel, a list, a map)

  • Flows: Triggers other MCP-enabled workflows in your workspace

  • Knowledge Bases: Pulls from stored documentation or reference material

When assigned to the node, these tools give the agent both the capability and the context it needs to autonomously decide what to use and in what order to fulfill the user’s request.

Begin by identifying the tools that your agent will use to complete a task:

Custom integrations

  • Select Resources from workspace menu > Choose Data requests

  • Add a new data request > Enter a descriptive name (no spaces or special characters) > Select Save

  • Provide Response model schema and/or Request model schema (if entering Request model schema, provide a description for each property so the agent understand what information is needed for the payload to successfully send the API call)

  • Provide a description on the Settings tab of the data request for the agent to understand the purpose of the tool > Click Save

Managed integrations

  • Select Integrations from workspace menu > Add a new integration

  • Enter a descriptive name > Choose integration type from Managed list

  • Complete required fields > Click Create integration

MCP-enabled flows

  • Select Flows from workspace menu > Add a new flow or select existing

  • Choose the flow's settings icon in the toolbar > Enter an AI description explaining the purpose of the workflow and toggle ON MCP option

  • Optionally, you can enter input schema for the flow's MCP properties that the agent will need to collect from a user before executing the workflow

  • Click Save

Modalities

  • Select Resources from workspace menu > Choose Modalities

  • Add a new modality > Select the auto-generate option to provide the output schema that your front-end will render went sent by the agent

  • Click Save

Knowledge bases

  • Select Resources from workspace menu > Choose Knowledge bases

  • Add a new knowledge base or select an existing

  • Choose type > Provide content or external integration

  • Provide a description in the settings > Click Save

Step 2: Use Generative Journey node in a flow

Est. time to complete: ~5 minutes

Identify the overall task your agent is completing and add a flow. Each flow is invoked when your chosen AI model identifies user intent from a user's utterance ("I want to order room service") and matches it to a flow you've created OrderRoomService. This match is done based on the training data you provide for your AI model.

  • Select Flows from workspace menu > Choose New flow

  • Enter a descriptive name (no spaces or special characters) > Select Save

  • Complete Flow setup by attaching training data and attaching slots

  • Place a Generative Journey node on the Canvas and attach it to the Start node

  • Click the Generative Journey node and choose Agentic on its configuration panel

  • Provide a succinct prompt to the LLM on what flow the task is part of, the end goal of the task, specific messaging or branding requirements (if any), and things to avoid (if any)

  • Provide the acceptable criteria for ejecting out of the Generative Journey node's Success path and proceeding a user through the remainder of a flow

  • Assign one or more tools from your workspace for the agent to use. Select the check icon after choosing each to attach it to the node

    • For any of Input schema (payload) your Tools require, you may swap between LLM prompt, Explicit values, or Placeholder variables for each property field by selecting the menu to the right of each field

  • Choose from one of the NLX-provided LLMs to power your agent's intelligence. Note that some models are better suited for specific tasks and communication channels

  • Link from the node's Success edge to the next node(s) in a flow (e.g., basic node, redirect node, etc.)

  • Click Save

🧠 Looking for more? See Generative Journey node

🧠 Looking for more? See Intro to flows

Step 3: Deploy application

Est. time to complete: ~2 minutes

Now you'll create the conversational AI application users will interface with. This step involves attaching all flows you want your application to access, defining flows to handle certain behaviors, setting up the channel(s) your application supports, and deploying.

  • Select Applications from workspace menu > Choose New application

  • Enter a descriptive name > Click Save

  • Click Flows tab of application > Select Attach flows > Attach one or more flows created in previous step to make available to your application > Click Attach selected then Save

  • Select Default behaviors tab of application > Assign any attached flows to the application's behaviors > Click Save

A build constructs the array of workflows that make up your application and updates any changes made to your flows, while deploying makes a successful build live:

  • Click Deployment tab of application > Select Create or Review & build

  • Wait for validation to complete > Select Create build*

  • When satisfied with a successful build, click Deploy

*After a build status appears as 🟢 Built, you may use the Test feature to test the conversation with your application using the latest build.

🧠 Looking to deploy on other channels? See Manage channels

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