Nodes
Get acquainted with nodes that construct your conversation flows in NLX
Add & connect nodes
All conversation flows consist of nodes that define logic, messaging, API calls, and turns that must be followed in a particular sequence. There are a variety of node types, each with their own function (e.g., routing a user, providing a message, listening for user intent, etc.).
Easily add a node to drop on to your Canvas using the toolbar or shortcut menu:
Choose Add option in toolbar or right-click to use New node in Canvas shortcut menu
Select node type to apply to the Canvas
Nodes are linked together via their node paths. Every node has one or more for each possible path the flow may take.
Connect the first node of your flow to the Canvas' Start node.
To connect nodes, click from a node's path > Drag line to recipient node
Disconnect nodes by clicking the line linking them or dragging a node away from a stack and selecting the linked line
Connected lines are blue and show directional flow. Dashed lines indicate recipient node is arranged behind or in line with the origin node on the Canvas. Moving a recipient node in front turns lines solid.
To tighten the space used on the Canvas, you may also stack nodes together:
To connect nodes through stacking, click and drag a node on top or bottom of another
A path turns into an arrow, indicating the flow's direction
To delete a node, select it and press delete or right-click and choose Delete from the shortcut menu.
Configuring nodes
Selecting a node on your Canvas reveals a side panel to display information about the node and provide options for adding or refining its actions. Clicking outside of the node automatically closes the panel.
Every node has a non-editable ID so the node may be referenced across the NLX workspace. To show the Node ID, click the info icon in the upper right of the node's side panel.
Node messaging
Not all nodes have a Messages section. You may use a Basic node before or after in these instances.
Your conversational AI relays messages to users when a node they've reached has Messages entered. Below are options to help enhance your use of this feature:
Select a node > Add messages to a node by clicking +Add message on a node's side panel
Repeat the above as often as needed on a single node
To delete a message, choose the three-dot menu beside the message and select Delete
NOTE: Adding more than one message to a node breaks up large messages into a series of smaller ones, making it easier for users to consume on text interfaces
Message variations do not get translated. If developing for multilingual AI applications, avoid using message variations.
Adding variations may be favorable when users regularly interact with the same conversational AI application or may traverse a node(s) in a flow more than once during the same session, such as with repeat processes or retries. The NLX NLU chooses from your variations randomly, so users experience different phrasing.
Select a node > After adding a message using a node's side panel, click +Add variation
To delete a message, choose the three-dot menu beside the message and select Delete
Easily reference variables in your messaging that is unique for each conversation:
Select a node > Select +Add message on a node's side panel
Enter a curly brace { while typing in a message field
If you do not see a Slot that exists in your workspace, remember to attach it within your flow's Settings. If you do not see a Data request variable from List schema, you may need to iterate over the list by placing a Loop node before your Data request node and setting it to List.
SSML tags are visible in text-based channels if reusing the same flow and sequence of nodes for both voice and chat. Use a Split node to branch the flow in those events.
When drafting messages for voice channels, you can use SSML tags (Speech Synthesis Markup Language) supported by your NLP. Inserting SSML into your messages can control volume, pitch, pauses, emphases, breathing, and more.
For Amazon Lex, check their supported SSML guide here.
For Google's Dialogflow CX, check their supported SSML guide here.
Add Basic nodes with messaging before custom API nodes (i.e., Actions, Data requests) to indicate a process is about to happen, particularly if it may take a moment
Be mindful of the placement of messaging in case a series of nodes (or stack) might be cycled through twice. You may want to add a Loop node set to Range that ejects after a certain count so the messaging from any nodes isn't repeated unnecessarily
Plan for failure when collecting information from a user or asking them to make a choice by adding failure messages with Basic nodes
Node functionality
Several advanced actions can be applied to nodes on the Canvas. Simply select+ Add functionality on a node's side panel and select from the following:
Assign tags to nodes for tracking and later evaluating their performance in your flow using Canvas analytics. While reviewing Canvas analytics, you can view the number of unique visits to the node from conversations with users.
Choose from three available system tags or create custom tags through the Analytics tags resource menu. Note that new tags applied to nodes are not retroactively applied to previous conversations with deployed flows.
Select a node > Click Add functionality menu on a node's side panel > Choose Analytics tags
Search or select a tag from the dropdown to assign to the node
Repeat as often as needed
To delete a tag, click the delete icon beside it
Requires creating at least one Modality in your workspace before referencing in a node.
Modalities allow you to reuse a pre-defined payload structure across flows of your workspace once enabled on a node of your choice. They can handle rich UI components or other information to relay to a user. NOTE: Modalities only display on end-of-turn nodes. Make sure the node is either a User choice, User input, Agentic Generative Journey, or not connected to any following nodes.
Select a node > Click Add functionality on a node's side panel > Choose Modality
Select a modality from your workspace in the dropdown
Enter payload details or assign dynamic sources into applicable fields > Click Save
Requires creating at least one user feedback collection before referencing in a node.
Collect feedback adds a structured user feedback mechanism to the AI's response (i.e., 👍/👎 controls). Because a feedback collection is a global workspace resource, you can reuse the same one across any end-of-turn node in your flow (i.e., User choice or User input node).
Select a node > Click Add functionality on a node's side panel > Choose Collect feedback
Select a user feedback collection from your workspace in the dropdown
Click Save
Node payload holds payload commands executed in conversation. Use cases include specifying what call queue should be used during escalation to an agent, whether to include a transcript during escalation, or sending a control message to NLP to allow users to interrupt the conversational AI, for example.
Select a node > Click Add functionality menu on a node's side panel > Choose Node payload
Specify each item as a key-value pair in the following format: key=value. To specify multiple items, use an ampersand (&) as a separator.
nlx_transferPhoneNumber
E.164 phone number
Amazon Connect
The phone number used to transfer to in the event of an escalation.
escalation_PSTN
E.164 phone number
Amazon Chime SDK
The phone number used to transfer to in the event of an escalation.
escalation_VC
Amazon Chime SDK Voice Connector URL
Amazon Chime SDK
The voice connector used to transfer a call.
x-amz-lex:*
Varies. Include =True at the end of your Lex syntax to enable; for example, x-amz-lex:allow-interrupt:*:*=True
Amazon Lex with a voice channel
Configure timeouts for user input, user interruption (barge-in), and other behaviors. Check out the official Amazon docs for supported syntax.
nlx:hints
A comma separated list of strings
Amazon Lex with a voice channel
Improve disambiguation over voice when there is an anticipated list of options.
Enabling Send context allows the conversation context variables to be included as a part of the response payload. If you are sending context to an API, it will be added to the payload response.
State modifications allow you to apply advanced state changes to dynamic variables from Slots, Context variables, System variables, or Data requests that are referenced in a flow:
Clear: Erases any specified variable(s) captured if needing to re-capture the same variables later (preventing auto-traversal), or if looping users back through a step(s) during retries or revisits in the same conversation session, including null, No match, or repeat instances
Set: Allows you to establish and set a specified variable from that point forward in the conversation session (until a further state modification is applied)
Increment: Automatically increases a specified numerical variable when the node containing the increment is visited. Useful with Split node logic and/or counting with a counter Context variable during retries; use in conjunction with the Set state mod if needing to establish the base value prior
Decrement: Automatically decreases a specified numerical variable when the node containing the decrement is visited. Useful with Split node logic and/or counting with a counter Context variable during retries; use in conjunction with the Set state mod if needing to establish the base value prior
Append to: Add one or more variables to a list/array
Remove last item from: Clear the last variable from a list/array
Leverage streaming state modifications applied to your Data requests during a conversation with use of a Lifecycle hook and enabling the Stream state modification setting.
Node types
Start
Start node is the home node of every flow. It's non-editable, provides information on how the flow is reached by users, and should be attached to the first node added to your Canvas.
Every flow or page created within a flow automatically populates a Start node as a beginning point. A node added to the Canvas can then be attached to Start through a line or by stacking
Next: Link to the first node added to the flow
Action
Use of this node requires setting up an Action in your workspace. This feature is currently available to enterprise tiers only.
Action nodes initiate an external task to occur.
An email or text sent to the user for a survey, confirmation, or set of instructions
Triggering the creation of a service ticket, work order, purchase, etc.
Scheduling an appointment or calendar meeting
Success: Link to the next node in the flow if the action executed properly
Optional:
Timeout: Link to a node if the action does not respond a status before the timeout
Failure: Link to a node if the action was not able to connect as configured
Invoke: Select from available Actions already created in the workspace
Payload: Each payload field is auto-generated by the Request model set up when the Action was created. Enter desired payload into each field(s), if applicable
Optional:
Always retrigger: Enable toggle to retrigger the action, even if the node is revisited again during the same conversation session
Timeout: Enable toggle to adjust timeout period in seconds. Default is 5s with a maximum of 30s
+ Add functionality: See Node functionality
Use a Loop node before the Action node to specify a number of retries allowed for failure events
Consider linking a Basic node to the Action's Success edge to acknowledge (via messaging) that the process was successful
Basic
Basic nodes are the easiest to include in any part of the flow. They can act as a messaging node, a processing node when given added functionality, both, or end a call when left unconnected at the end of a flow.
Indicate via message that a process is about to occur before continuing the flow
Offer a greeting or confirmation before/after a question or capture step
Clear a variable (from a slot or Data request source) in a retry cycle for a User choice node
End the call or conversation by leaving the node unattached
Next: Link to the next node in the flow, or leave unconnected to end a conversation call
Optional:
+ Add message: Add one or more message that is relayed to the user when reaching this node
+ Add functionality: See Node functionality
Add to the end of a flow to properly end a conversation with a user using a goodbye message
Link No match path to a Basic node, which can explain to users why something may have been an incorrect choice or incorrect input before continuing with a retry or escalation
Data request
Data request nodes allow you to trigger an API request during a conversation to execute a specific external action or send or retrieve data for use in a conversation. These nodes are strategically placed in a flow to run call(s) when needed.
Managed mode
Managed mode allows you to assign an API request from a managed integration service set up in the workspace that triggers when the node is traversed in the flow.
Use of this mode requires first setting up a managed integration in your workspace.
Create a calendar event
Push a post to a social media platform
Generate a ticket in a CRM system
Success: Link to the next node in the flow if the request executed properly
Optional:
In progress: Link to a node that loops back to the Data request node while a request call is being resolved; useful to avoid timeout restrictions from voice channel providers on API calls that take longer. Subject to the maximum timeout of 30s
Timeout: Link to a node if the request does not respond a status before the timeout
Failure: Link to a node if the request was not able to connect as configured
Ensure toggle is set to Managed
Provider: Choose from managed service providers
Action: Choose from the available actions related to the selected service. The list updates automatically when a different provider is selected
Resolve to: The output name that may be referenced in the rest of the flow (includes any nested variables retrieved from the API call). No spaces or special characters
Optional:
Settings
Custom timeout: Enable toggle to adjust call timeout period in seconds. Default is 5s with a maximum of 30s
+ Add functionality: See Node functionality
Place a Data request node BEFORE other nodes in a flow that must relay, reference, or use conditional logic based on the properties sent/retrieved or event executed by your Data request
Reference information in text fields by entering an open curly bracket
{and selecting from Data requests in the workspace. Managed integrations and their variables (properties) are color-coded purple
Custom mode
Custom mode allows you to assign a Data request from your workspace that triggers the custom API request when the node is traversed in the flow.
Use of this mode requires first setting up a custom Data request in your workspace.
Checking available rooms to assist with a hotel reservation
Pulling a list of local restaurants to match a user's criteria
Fetching the user's profile to authenticate and customize the conversation
A payload of information sent to a database for storage or updating (e.g., user profiles, passwords, etc.).
Success: Link to the next node in the flow if the request executed properly; generally follow with a node where the Data request or properties of the Data request are being referenced
Optional:
In progress: Link to a node that loops back to the Data request node while a request call is being resolved; useful to avoid timeout restrictions from voice channel providers on API calls that take longer. Subject to the maximum timeout of 30s
Timeout: Link to a node if the request does not respond a status before the timeout
Failure: Link to a node if the request was not able to connect as configured
Ensure toggle is set to Custom
Request: Choose from any custom integration (data request) created in your workspace
Optional:
Payload: Specify the payload to be retrieved; fields are set up under the Request model when creating the data request
Always retrigger: Enable toggle to retrigger the data request, even if the node is revisited again during the same conversation session
Custom timeout: Enable toggle to adjust timeout period in seconds. Default is 5s with a maximum of 30s. If increasing the timeout for custom webhooks, link the node's In progress connector to a Basic node that then links back to the Data request node. This avoids a premature timeout imposed by your communication channel before your request call is resolved
+ Add functionality: See Node functionality
Place a Data request node BEFORE other nodes in a flow that must relay, reference, or use conditional logic based on the properties sent/retrieved or event executed by your Data request
Reference information in text fields of other nodes by entering an open curly bracket
{and selecting from Data request properties. Custom Data requests and their schema are color-coded orangeIf you do not see properties from your schema in the placeholder menu, they are likely defined as an array. Link to a Loop node set to List and assign your Data request to process and extract them for reference
If increasing the default timeout in the side panel for API calls that take a while to resolve, it's recommended that you link the Data request node's In progress connector to a Basic node with "One moment..." messaging that then links back to the Data request node. This avoids a premature timeout imposed by your voice provider channel before your request call is resolved and provides for a better user experience
Define
Define nodes allow you to define and set ephemeral values for use in a single flow. In essence, they work similarly to Context variables but are instead localized to a single flow and do not persist beyond the flow.
A value captured or set in a flow that shouldn't be retained outside of the current flow
A value captured from the user must carry a different meaning in other flows in the same conversation session
Parsing date to extract its component parts (minutes, seconds, hours, days, etc.). See How-to tab for instructions
Next: Link to the next node added to the flow
Output variable: Give the defined value a name that's used whenever referenced in the flow downstream (no spaces)
Simple / Schema toggle: Swap between defining a simple value property or a schema
Value: Set the value's meaning (swap the property type from the right of the dropdown). If swapping to dynamic property type
{x} Placeholders, select from those in the workspace using the dropdown
Optional:
If defining a value set from
{x} Placeholders, you may also choose an operator to the left of the dropdown field to manipulate the value:
First: Grabs the first element of a Data request Response body set to List
Length: Sets the value to the number of items in a list or the number of characters, including whitespace, in a string [e.g., LENGTH("12345") returns 5]
Increment: Increases the value by +1
Decrement: Decreases the value by -1
Lowercase: Converts a value to all lowercase styling
Trim: Removes leading or trailing whitespace characters
Lowercase + trim: Converts a value to all lowercase styling and removes leading or trailing whitespace characters
Parse date: Extracts all date components from a value (millisecond, second, minute, day, hour, ISOstring, month, year, timezone, timestamp)
+ Add functionality: See Node functionality
Use Define node with Parse date for dynamic messaging specific to your flow
Example: A user sets up an account that also provides them monthly rewards for being an active member. The slot type
NLX.TextorNLX.Datecaptures a user providing an activation date of 11/15/2023 through a User choice node. Follow with a Define node to name the value 'Rewards' and define it as a parsed date of the activation date slot. Later messaging can choose to reference it as "Your monthly reward will be sent on day{Rewards.day}of every month!" = "Your monthly reward will be sent on day 11 of every month!"
Escalate
Escalate nodes immediately initiate the escalation transfer for the flow's communication channel.
Use of this node requires an escalation channel set up in your workspace Settings.
Business procedure requires that a user change their registered email with an agent only
Your conversational AI is not yet enabled with the ability to perform a task requested by the user
Technical processes involving APIs/webhooks failing
Optional:
Timeout: Link to a node if the escalation does not transfer before the timeout
Failure: Link to a node if the escalation was not able to connect as configured
Continuation: Link to the next node of the current flow if the escalation returns to the conversational application
Optional:
+ Add message: Add a message(s) that is relayed to the user when reaching this node
+ Add functionality: See Node functionality
You may either reuse the Escalate node anywhere in a flow or link to the same Escalate node from anywhere in the flow
In some instances, you may wish to develop an escalation intent that handles an extended process before ending with the Escalate node (e.g., authenticating a user, sharing current wait times, or presenting a final pitch to complete a task with the conversational AI instead of an agent)
Generative Journey® v2
Generative Journey® v2 nodes allow you to employ a large language model (LLM) to collect several variables from a user and execute multiple tools as part of a cohesive task with multiple exit conditions you can define. Tools you can assign include custom APIs set up through Data requests, managed APIs set up through Integrations, modalities, knowledge bases, or flows. Your agent will determine when to call tools based on the overall prompt you provide.
Restaurant ordering: Collect name + order, call ordering API, send confirmation SMS/email
Travel servicing: Collect record locator + passenger name, check eligibility, cancel flight, confirm changes
Support automation: Collect issue + account identifier, call ticketing API, summarize and file ticket, confirm
Exit conditions: Add and briefly define one or more outcomes that could occur to exit the node, link to the next node in the flow
Data capture: If slots are entered that the agent must capture AND Exit when complete is enabled, link to the next node in the flow
Optional:
Timeout: Link to a node if the agent or tools do not respond before the timeout
Failure: Link to a node if the agent or tools were not able to connect as configured
Prompt: A prompt given to the LLM agent that identifies the context of the overall task and the required information to extract. Brand voice guidelines and additional rules may be provided
+ Add exit condition: Add one or more acceptable endings that helps the agent determine when to eject from the node and where the conversation will proceed through the remainder of a flow
Tools: Assign one or more managed data requests from Integrations, custom Data requests, flows, modalities, or knowledge bases from your workspace for the agent to use. Expand a tool after adding it to include a brief prompt for using the tool
For any 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
Add an optional Interim message: The agent will deliver this message before a tool is called (e.g., "Let me take a look," or, "One moment while I check"). Expand an attached tool to add
Input schema property fields with description dropdown options Managed data requests: Choose the applicable action you want executed for that service. Expand the tool after adding to enter a tool prompt (when to use and any additional guidelines not explained in the general prompt) as well as applicable payload variables
Custom data requests: Expand the tool after adding to enter a tool prompt (when to use and any additional guidelines not explained in the general prompt) as well as applicable payload variables
Flows: Choose from any flows in your workspace that will act as a subroutine for the agent. Expand the tool after adding to enter a tool prompt (when to use and any additional guidelines not explained in the general prompt)
NOTE: Add a Redirect node at the end of each flow tool where you want to return back to the Generative Journey agent > On the redirect node, choose the flow where the Generative Journey node exists, choose Custom node, and enter the Generative Journey node's ID (select the three-dot menu on the GJ node to copy the ID)
Modalities: Choose from modalities created in your workspace. Expand the tool after adding to enter a tool prompt (when to use and any additional guidelines not explained in the general prompt) as well as applicable payload variables
Knowledge bases: Expand the tool after adding to enter a tool prompt (when to use and any additional guidelines not explained in the general prompt)
Data capture:
Required slots: Include required slots that the agent must collect from a user (e.g., check-in date, checkout date, number of guests, number of rooms, etc.). Only slots attached to the flow appear for selection
Optional slots: Include optional slots the agent should incorporate if the user provides them (e.g., preferred room, number of pets traveling, etc.)
Exit upon completion: Creates an automatic node pathway (similar to an exit condition) that can be linked to the rest of the flow. The pathway will be triggered after all resolved slots are collected
LLM Model: Choose from one of the provided models to power your agent's intelligence. Note that some models are better suited for specific tasks and communication channels:
Amazon Nova Lite: A fast inexpensive model that is great for simple tool calls over voice
Anthropic Haiku: A balance of speed and accuracy well-suited for most tool calls
Anthropic Opus: A slower but more powerful model for complex tool calls; best for chat-based applications
Cerebras OSS 120B: The fastest inference mode; best suited for low-latency applications
Custom model (enterprise only): Select the LLM service integrated in your workspace to power task execution
Settings (expand menu):
Max steps: Limits the number of internal processing steps before a response is generated
Zero-turn mode: The LLM will resolve any required variables for task completion detected in the last logged user utterance and automatically exit from the Success path
Timeout: Set a custom time limit (in seconds) for how long the LLM has to respond before it times out
+ Add functionality: See Node functionality
Check out our Guide to implement Generative Journey.
Add and connect a Generative Journey v2 node to your flow
Write the prompt: task + constraints + what completion means
Add tools (KB, data requests, flows, modalities) and provide brief tool prompts
Add Data capture slots if the task requires structured values to be collected from the user
Add exit conditions for the outcomes you want your agent to account for
Link all node paths to the next nodes (ending, timeout, fallback, etc.)
Test in the sandbox and refine prompts, tool descriptions, and exit conditions
Generative text
Generative text nodes employ a large language model (LLM) to generate virtually any output, including crafting messages, applying logic, or quickly reformatting information based on provided context of the conversation.
Use of this node requires a one-time LLM integration in your workspace Settings.
Generate required messaging dynamically (welcome message, apology, error, etc.)
Provide rules to generate logic based on given input and check in a Split node for the result
Reformat a date or do quick math
Success: Link to a node that then references the name given in the Generate field to provide the generated output. Use the open curly bracket in any text field of a subsequent node in the flow
{
Optional:
Timeout: Link to a node if the LLM does not respond before the timeout
Failure: Link to a node if the LLM was not able to connect as configured
Prompt: The prompt given to the LLM that specifies what generated output you'd like
Output variable: Provide a simple name or acronym to use the generated output downstream as a variable locally in the flow (no spaces)
Integration: The workspace integration name for the LLM being used
Temperature: Controls randomness of word choice in generated text. Lower values (e.g., 0–0.3) are more deterministic; higher values (e.g., 0.8–1.2) are more creative and variable. Default is set to 1
Max tokens: The upper limit on the model’s output length (in tokens). If reached, the response is cut off. Default is set to 4000
Optional:
Settings (expand):
Include transcript as context: When enabled, transcript of the conversation between your conversational AI and user up to that point is sent to the LLM along with the prompt for added context
+ Add functionality: See Node functionality
Place a Generative text node on the Canvas > Using the node's side panel, assign an LLM integration previously set up in the workspace
Enter a name for the prompt using the Generate field (this name will be referenced in the flow when wanting to trigger the LLM in conversation) > Provide a succinct prompt to the LLM in the Generative text node within its Prompt field
Add a node with messaging (in this example, a standard Basic node is used) and link the Success edge of your Generative text node to the new node
Click + Add message on your new node and enter the placeholder name given to the Generative text prompt using the open curly brace { menu
Good AI prompts include an explanation of the AI's purpose, a prescribed limit to the length of its responses, and any topics or words it should avoid
Knowledge base
Knowledge base nodes allow you to invoke a response from a digital library of information. They're valuable in answering questions or relaying information to users on common topics that don't require multiple flows to address.
Use of this node requires setting up a Knowledge base in your workspace.
Provide common FAQ responses on policies, service offerings, and helpful links (if chat) to guide users
Provide instructions and how-tos on topics for staff or customers
Match: Link to a node in the flow when the user utterance was matched to data in the knowledge base. Generally follow with a Basic or User choice node containing the variable
{GenerateName.answer}in its messaging to provide the responseNo match: Link to a node in the flow when the user utterance was not matched to information in the knowledge base
Optional:
In progress: Link to a node (may contain progress message or silence breaks) that then loops back to the Knowledge base node while a request call is being resolved; useful to avoid timeout restrictions from voice channel providers on API calls that take longer. Be sure to also define a custom timeout under the Knowledge base node's Settings
Timeout: Link to a node if the request does not respond a status before the timeout
Failure: Link to a node if the request was not able to locate a response from the user's utterance
Question: Add the variable necessary to aid the AI model in its answer search (default is
{System.utterance}. Provide context if sending more than one variable (e.g., the user is a{userProfile.RewardsTier}member and wants to know about{system.Utterance})Knowledge base: Select from available knowledge bases created in the workspace
Prompt (optional): If desired, provide specific instructions, rules, brand voice, additional variables, or other guidelines to follow when your conversational AI relays answers from your knowledge base
Output variable: Provide a simple name or acronym to use the knowledge base response as a variable locally in the flow (no spaces)
IF filters: If Metadata has been provided when setting up a Q&A- or External-type Knowledge base, you may provide IF comparison statements ("IF x equals y") when referencing any properties of your metadata schema. This will be sent along in the retrieval request as a filter when your Knowledge base is called
Optional
Settings (expand):
Auto-translate: Enable toggle to translate the programmed response to the detected language of the user
Timeout: Enable toggle to adjust timeout period of answer retrieval in seconds. Default is 5s
Include citation: Enable toggle to include in-line citations with responses. Must use a modality to render citations on a User choice or User input node linked from the Match edge
Custom minimum confidence score: Enable toggle to adjust the minimum confidence score previously set at the application level; only impacts response and utterance matching done through knowledge base interaction. Supported through Q&A implementation of knowledge base content
+ Add functionality: See Node functionality
Add a Knowledge base node to the Canvas
On the node's side panel, enter
system.Utterance(or any relevant variable type you wish to use) in the Question field and assign a Knowledge base from your workspace in the dropdownLink a Basic node from the Knowledge base node's Match edge > Enter the placeholder
{"yourKBname".answer}as a message on the Basic nodeProceed from the Basic node to either redirect to another flow, capture user intent, or provide a selection of choices to a user to help with follow-up after an answer has been relayed
Click Save
Loop
Loop nodes help to either set an allowed number of retries for a user's response or an API call (such as with a Data request or Action), or they can help survey items in a data array (set to List schema).
Range mode
Prevent infinite looping by allowing one retry for a user to provide their PIN before escalating to an agent
List mode
Loop over a list of resorts and provide matches from a user's preference of 5-star establishments in Tokyo
Next: Link to the next node in the flow (usually a Data request node for processing an array [list schema] or User choice or User input for setting input retries)
Completed: Once the loops have concluded without a desired result, the flow ejects to an another node that may handle the fail state (Escalate or Redirect, for example)
For each: Give a name of the loop iteration (e.g.,
RetryorName.UserProfile)+ Add functionality: See Node functionality
Range mode:
From/To: Enter range of allowed looped retries before ejecting from the Completed edge
List mode:
From: Select Data request and data property (if applicable) to be used as the array for scanning and retrieving. Your Data request's high-level Response model type must be set to List
Stack or place a Loop node before a Data request or User choice node
Use State modifications on either the Loop node or a node that precedes the Loop in a retry cycle to Clear the user selection. This prevents retaining information from the first pass and creating repeated No match incidents
Note
Notes are for adding freeform text to the Canvas and do not impact the conversation flow. From the Canvas shortcut menu (right-click anywhere on the Canvas) or by selecting Add note from the small toolbar menu, you may add a text box for internal-facing text.
Provide instructions or explanations to a teammate about items on the flow
Document different node stacks or sections of a flow for organization or visual mapping
Enter descriptions or thoughts about areas or whole pages of a flow
Notes are not designed for use in a flow and therefore have no connecting paths
Body: Enter note message in this field. You may also reference dynamic values created in the workspace with an open curly brace {
Optional:
Title: Enter a brief title to describe the note or call attention to it
There's no wrong way to use Notes, but you can explore more ways to stay organized
Redirect
Redirect nodes route users to to a different page of a flow or to a different flow.
An unregistered user that needs to complete a profile before proceeding with the main flow (redirect to a page of the same flow or another flow)
After asking a user what they need help with (User input node) and routing them based on a matched training phrase
Moving a user from a flow covering booking policies at a resort to a flow that books a resort reservation
Optional
Continuation: Link to the next node of the current flow if the redirect returns back to this point
Page: If multiple pages of an intent's flow exist, specify which page to take the conversation
Flow: Select from other flows available in the workspace
Recognized flow: The captured utterance from a preceding User input node is matched by the NLP to a training phrase of a flow attached to the application
Previous redirect: Goes back to a previous Redirect node that last did a reroute in the conversation and continues the flow
Parent application: Transfers back to the original application if currently in a new application's flow from an application handoff scenario
Optional
+ Add functionality: See Node functionality
Ensure if multiple flows are referenced that all are attached to the application before deployment
Only choose Flow over Flow recognized when certain the new flow accomplishes the user's need based on their set of choices or path taken. Flow recognized is active user navigation while Flow drives the direction without the user
Split
Split nodes divide users in a path flow based on either a set of defined criteria (conditions) or through chance distribution.
Conditions mode
Conditions mode allows you to control the pathways of a conversation based on provided conditional logic that can be defined manually as IF statements or using an LLM with a simple logic prompt.
Diverting the flow to new messaging or processes based on the channel type users are communicating through (e.g., Twilio Voice vs API). Use with the system variable
channelTypeSort users based on different variables (e.g., rewards level, credit card type, authenticated, etc.)
If condition: Each path appears as conditions are added to the Split node. Each path may be linked to a different node specified in a flow
Optional
else: Link to a node in the flow when any established conditions(s) are not matched
If condition: Each dropdown provides options to craft a conditional statement. You may also use the + And link to add more modifiers to a statement and create a single grouping of conditions
Generative IF condition: Provide a prompt for each generative condition that must be met (e.g, "If user's intent is to find out about our rewards program but they are not currently a member. Intent:
system.Utterance. Member profile:user.Profile"). Requires selecting the LLM integration (may use built-in NLX LLM)
Optional:
+ Add functionality: See Node functionality
Enter a name for each If condition on the side panel. When collapsing the node on the Canvas, only the name of the group appears, decluttering large Split nodes and providing better visual organization
Adding separate conditions on a Split rather than one grouping indicates that if the first condition isn't met, it will proceed to the next condition
The NLX NLU processes each condition in the order they appear in the side panel, so reorder them as desired using the three-dot menu next to each condition
Chance mode
Chance mode randomly routes users to different paths based on assigned percentages.
Conducting A/B testing on new messaging or new process and diverting a portion of user traffic to test
Chance: Each path appears as chance conditions are added to the Split node. Each path may be linked to a different node specified in a flow
Optional
else: Not applicable in Chance mode
Select + Add condition to create multiple splits in traffic that divert a percentage of users for each pathway. Percentages may be adjusted manually using the slider or may be calculated evenly across pathways by clicking Distribute equally
Optional:
+ Add functionality: See Node functionality
Transform
Transform nodes reshape, filter, or remap data retrieved from data requests, context variables, or knowledge base citations. They let you apply deterministic logic or generative reasoning to restructure arrays, filter items, or convert data into the exact schema needed for flows, modalities, or agentic tools.
Filtering a list of items (e.g., showing only Window or Aisle seat options)
Removing unavailable or irrelevant results before a user sees them
Reshaping raw API data into the schema required by a modality (e.g., carousel cards)
Adding or modifying properties (e.g., appending
"isVIP": truefor recognized customers)
Next: Link to the next node added to the flow
Input variable: Select the source variable you want to transform
Output variable: Name the transformed output so it can be referenced easily downstream in the flow
+ Add transformation: Choose one or more transformations to apply:
Filter: Apply one or more IF conditions to keep only items that match your criteria. Example:
seatType == "Window" OR seatType == "Aisle"Generative filter: Use an LLM to evaluate or classify items in the list based on a prompt. Great for fuzzy or semantic filtering (e.g., “return only packages that include breakfast”).
Map: Provide a desired schema, and manually rewrite each individual item in the input list to match that schema. Ideal when input and output shapes differ on a per-item basis or require semantic interpretation
Generative map: Provide a desired schema, and an LLM automatically rewrites each individual item in the input list to match that schema. Ideal when input and output shapes differ on a per-item basis or require semantic interpretation. Need to restructure an entire dataset, aggregate items, or perform a transformation that isn’t one-to-one? Use Morph instead
Morph: Morph allows you to rewrite an entire list of data into a completely new structure using freeform instructions. It uses an LLM to reshape the data based on a natural-language prompt and a selected output schema
Sort: Sort a list in ascending or descending order by a particular value in the data structure
Optional:
+ Add functionality: See Node functionality
User choice
User choice nodes prompt users to either make a selection or provide information for your conversational AI to follow-up with a relevant action, such as routing, refining, or externally passing along the info.
For User choice nodes, the NLX NLU will attempt the following (in order):
Match the user's utterance to a value from the assigned source (custom slot, built-in slot, or Data request array)
Match the user's utterance to training data belonging to other flows attached to the application
Eject out of the No match edge (if no logic or messaging is connected, the NLU will default to Unknown or Fallback)
Requires: Attaching a slot to the flow or setting up a Data request to assign a variable that the node will extract from a user.
Ask a user for the start date of their reported service outage
Ask a user a Yes/No question
Ask a user to choose from their available credit cards on file
Ask a user to provide a short explanation of their complaint
Match or value pathjs: Link to the next node in a flow based on the user's selection. May set node's pathways to mirror a Slot's values (max. 10) and direct each path to different nodes, or simplify with Match/No match paths
Optional
No match: Link to a node in the flow when a user's choice is invalid
Options: Choose from Slots that are attached to the current flow or from Data requests that exist in the workspace
+ Add message: Add a message(s) that is relayed to the user when reaching this node
If assigning a Data request to your User choice node, first invoke it using a Data request node and ensure the Data request's overarching Response model type is set to List)
Optional
Elicitation (visible on voice channels only): Indicates a user provide their choice by spelling it letter by letter (e.g., A, B, C) or spelling by words (e.g., A as in apple, B as in boy)
Additional slots: NLX Boost must first be enabled on your application before using this feature. If the user's choice does not match any of the primary options, your application will resort to one or more built-in slots attached to the flow and assigned on the user choice node. Choices matching options from additional slots will exit out of the No match edge but a Split node may be linked to check if they exist. See How-to tab for context
Settings (expand menu):
Show choices: Displays values (max. 10) in chat or reads them aloud in voice for users to choose
Auto-select only choice: If only one choice is available, the conversational application will make the selection on the user's behalf and automatically traverse to the next node in the flow
Reset choices to match/no match (visible when using a custom slot): Reset node connectors to Match/No match values
Reset choices to values (visible when using a custom slot): Reset node connectors to the individual slot values + No match
Choice label (visible when resolving from a Data request source): allows you to specify the Data request property to display for user selection. The Data request's overarching Response model type must be set to List
+ Add functionality: See Node functionality
If reusing a slot or data request's values in another User choice node in the conversation, be sure to place a Basic node beforehand that uses a State modification to Clear the user's previous selection. Otherwise, the application will retain the user's choice and auto-traverse through the second User choice node believing it to be the same
If applicable, link the No match edge to a Basic node that Clears the selection, explains why a response may be invalid, and links back to the User choice node to allow a user a retry
Additional slots are useful in cases where a user's selection would normally be supported despite their selection not matching choices from the initial primary source. For example, a user may be provided three available appointment options for today's date from a Data request source, but the user instead requests an appointment for tomorrow. An additional system slot, such as
NLX.DateorNLX.Text, may be assigned to the same node to handle this request. The user's request will follow along the No match edge on the node where a Split node should be used to detect if an additional slot(s) entry exists and proceed from there
User input
User input is considered a listening and capture node for collecting a user's utterance to match to an flow's training data or collecting a keyword(s) that alters or routes the conversation using Split node logic.
Asking a user what they need help with and routing them to a flow that matches training data
Asking a user an open-ended question to detect keyword(s) and route them using a Split and Redirect nodes
Flow recognized: Link to a node, usually Redirect, that routes a user to a flow based on their detected intent (flow recognition is provided to your AI model via the training data set on each flow)
No flow recognized: Link to a node in the flow when a user's intent is unrecognized
+ Add message: Add a message(s) that is relayed to the user when reaching this node
Optional:
+ Add functionality: See Node functionality
Be sure to assess the efficacy of training data for all flows attached to an application. This ensures the steps in flows that direct users with User input nodes work as intended
Voice+™
Starts Voice+ in the current conversation and activates the selected interaction mode.
Agentic mode
Agentic mode is for enabling bi-directional voice+ experiences in web or mobile via the NLX Touchpoint SDK, allowing the user to speak naturally and the AI to take on-screen actions.
For an easy agentic starter application, choose the Voice+ application type for a readymade app you can install on your frontend in minutes.
A user starts a webchat session that can navigate webpages, complete forms, and answer FAQs, all through a hands-free, voice-driven experience
Enable the corresponding action if also using a scripted Voice+ experience to support the Continuation or Escalation paths.
Optional:
Continuation: Link to the next node in the flow to continue from your Voice+ experience. (Only applicable if also using a Voice+ script.)
Timeout: Link to a node if the agent does not respond after the timeout period
Escalation: Link to the next node in the flow to begin an escalation process or trigger an immediate transfer using an Escalation node. (Only applicable if also using a Voice+ script.)
Tools: Assign one or more custom Data requests, managed data requests from Integrations, modalities, knowledge bases, MCP-enabled flows, or Data capture from your workspace for the agent to use. After adding, choose the applicable resource from the dropdown.
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.
Managed data requests: Choose the applicable action you want executed for that service. Select the check icon after choosing to attach it to the node. Expand the integration after attaching to enter a tool prompt and describe the purpose of the tool. Input schema has default descriptions, but you may provide additional rules in each field, if desired
Custom data requests: Select the check icon after choosing to attach it to the node. Descriptions should be provided on the Settings tab of the Data request to provide context to the agent, as well as descriptions on individual properties of the Request model schema properties. This helps the agent determine what information is to be collected, sent, and in what order to execute. Input schema defaults to the descriptions provided on the Request model properties of your data request, but you may provide additional rules in each field, if desired
Flows: Choose from available MCP-enabled flows in your workspace. If you cannot locate a flow you would like the agent to call, be sure to provide an AI description and toggle ON MCP in the flow's settings. Input schema defaults to the descriptions provided for the flow's MCP properties, but you may provide additional rules in each field, if desired
Modalities: Choose from modalities created in your workspace. Optionally select other tools as one or more triggers that must be completed before the modality is sent. Input schema, if applicable, defaults to the descriptions provided for the modality's properties, but you may provide additional rules in each field, if desired
Knowledge bases: Defaults to the description provided on the knowledge base's general settings, but you may provide additional rules, if desired
Data capture: The AI extracts variables from users that are defined as either variables from a Data request (must also attach as a custom data request tool) or slots
Actions: Add one or more Custom, Form fill, or Navigation actions that your agent can do on your web or mobile app. Using the Touchpoint SDK, you can define the scope tags of the pages where the action is permitted
For Custom actions, like filtering, checking radio boxes, selecting, etc., you may provide the name of the action and a prompt for when to apply the custom behavior. Enable the Custom schema toggle to enter output schema that's sent to your frontend
Optional:
Settings (expand):
Session start timeout: The amount of time (in seconds) to wait for the user to trigger the first Voice+ script step from your digital asset (web or mobile application), if also using a Voice+ script
Inactivity timeout: The amount of time (in seconds) to wait for a user to proceed between Voice+ script steps, if also using a Voice+ script
+ Add functionality: See Node functionality
Scripted mode
Scripted mode is for enabling exclusive use of Voice+ scripts, which synchronizes predefined unidirectional voice prompts over an active phone call with visual assets from your web or mobile application.
A user calling to request a service during heavy call volumes is texted a link and guided through completing an online form
Enable the corresponding action on a Voice+ script step to support the Continuation or Escalation paths.
Optional:
Continuation: Link to the next node in the flow to continue from your Voice+ experience (generally triggered by the last step of your Voice+ Script)
Timeout: Link to a node if the Voice+ step does not respond after the timeout period
Escalation: Link to the next node in the flow to begin an escalation process or trigger an immediate transfer using an Escalation node (generally triggered by an appropriate step requiring agent transfer in your Voice+ experience)
Optional:
Settings (expand):
Session start timeout: The amount of time (in seconds) to wait for the user to trigger the first Voice+ script step from your digital asset (web or mobile application)
Inactivity timeout: The amount of time (in seconds) to wait for a user to proceed between Voice+ script steps. Default is 10 minutes
+ Add functionality: See Node functionality
To set up predefined Voice+ scripts: Check out this guide
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