Make your AI agents predictable.
Define the critical steps, connect the right actions and plan for exceptions. Test the paths before publishing a flow your team can understand and improve.
Talk to salesConfirm service details
Prepare availability lookup
Powering businesses, agencies and franchise operators.
Household-brand logos represent franchise-level deployments.
Put structure around the moments that matter.
Give your agent a clear path through critical decisions, business actions and exceptions.
Break a broad instruction into focused steps. Confirm the service and preferred day before moving to availability, so your team can see what each part of the conversation is meant to do.
Use conversational conditions for intent. Use Logic to compare values already collected, with ordered branches and an Else path for missing information.
Connect the calendar tool to the step that needs availability. Collect its required context first, then design separate paths for returned information and an unavailable result.
Give unclear answers, unavailable tools and requests for a person somewhere to go. Connect human help to a configured transfer tool, with a plan for an unanswered destination.
Configuration example
Choose where the agent can decide.
Use model judgment where conversation needs it. Use explicit comparisons and connected actions where the process demands them.
- Instructions for each step
- Conditions for each branch
- Actions connected to your systems
Instructions for a generated response.
Control the response.
Write a focused prompt or supply fixed text for the first visit. Keep shared guidance in the Global Prompt.
preferred_dayis setContinue to availabilityDeterministic comparison of an existing value, with an Else path.
Match the rule to the decision.
Interpret intent with conversational conditions. Route known values through Logic branches and a defined default.
service_typepreferred_dayOffer only the returned times.
Plan beyond the happy path.
Collect the context your tool needs. Define how the conversation continues when a result is available, empty or unavailable.
Illustrative configurations. These controls do not run a model, call a tool or change a live agent.
Know the path before you publish.
Exercise the draft. Review the changes. See the steps and tool responses that explain what happened.
“I'd like to arrange a service appointment.”
The customer wants to book a new appointment.
Collect the service and preferred day before checking availability.
Ask which service the customer needs before checking the calendar.
Restore to the editor. Review, then publish.Which times are available for a service visit?
Qualify requestCheck availability
service: maintenance
day: requested dayavailable_slots: []No times returned in this example.From critical workflow to controlled release.
Talk to salesDesign the critical paths
Map the decisions that matter. Define what each step collects, which actions it can take and where exceptions go.
Test the expected and unexpected
Try complete requests, missing details and unclear intent. Review the chosen paths, then verify tools on the actual channel.
Publish the reviewed version
Keep edits in a draft until your team is ready. Publish the flow, then select it in the assistant’s LLM settings.
Control the path. Review the changes. Learn from the record.
- Defined paths
- Managed releases
- Conversation review
Flow Builder
questions.
How does a flow make an AI agent more predictable?
A flow gives each step a defined purpose, available tools and explicit paths. Your team can see the process, test its branches and review the recorded conversation. That makes behavior easier to control and investigate; it does not make every model response or external system infallible.
Which decisions are deterministic, and which use an LLM?
A Logic node can evaluate configured rules against variables. Conversation paths can use a model to interpret a customer’s words. Use rules for business decisions with exact criteria, and model-based conditions where intent needs interpretation. Test both, especially when information is missing or ambiguous.
What happens when a tool cannot complete an action?
Define the required inputs, inspect the returned result and configure what happens when the request cannot be completed. The right response might be another question, a different path or a human handoff. Do not treat an attempted tool call as a confirmed booking, payment or update.
Can a person take over when the flow reaches its limit?
Yes. For a live phone call, use a configured transfer tool and the correct destination. Make the escalation condition part of the flow, then test availability, unanswered calls and the customer experience. Handoff behavior depends on the channel and transfer setup.
How should we test a flow before customers use it?
Try expected requests, unclear intent, missing details and unavailable services in the editor. Inspect the chosen path and available tool records. Then test the assigned assistant on the actual phone or website channel. An editor conversation alone does not verify audio, routing, embedding or every external action.
Can we change or restore a published flow?
Work on the draft, review the changes and publish when your team is ready to update the live flow. Version History can restore an earlier design to the editor. Review and publish that restored design as needed; restoring an editor version is not the same as confirming a live rollback.
Can we use the flow on both calls and website chat?
Publish the flow, then select it in the assistant’s LLM settings. For calls, connect that assistant to the intended phone configuration. For website chat, connect it to the widget. Validate each channel separately: voice transfers, audio and website interactions do not have identical requirements.
Put your process in control.
Turn your critical workflow into a clear path your team can test, release and improve.
Talk to sales