maestro
latest
false
Maestro user guide
- Introduction
- Getting started
- Building with Maestro BPMN
- Understanding Maestro BPMN modeling
- Opening the modeling canvas
- Modeling your process
- Aligning and connecting BPMN elements
- Autopilot for Maestro (Preview)
- Process Repository
- Implementing a simple BPMN process
- Implementing a complex BPMN process
- Debugging
- Simulating
- Common implementation scenarios
- Building with Maestro Case
- Introduction to Maestro Case
- Maestro BPMN vs. Maestro Case: when to use case management
- The Maestro Case lifecycle: from event trigger to app experience
- Build your first case with Maestro Case
- Build a Maestro Case with a coding agent (preview)
- Defining case keys (system vs. external)
- Establishing task I/O and write-back contracts
- Exit rules and early stage termination
- Modeling primary and secondary stages
- Triggering a case from Data Fabric
- Implementing stage-level personas and permissions
- Setting SLAs and automated escalation rules
- Configuring a rework loop (re-entry)
- Configuring and testing the Case Manager Agent (preview)
- Case Manager input and output contract
- Maestro Case component dictionary
- Building with Maestro Flow
- Integrations
- Operating
- Monitoring
- Optimizing
- Reference information
Chat nodes for modeling conversational experiences in Maestro Flow, covering routing control, conversational AI turns, and deterministic messages.
The Chat nodes build a conversational Flow. Once deployed, it reaches end-users through every chat channel supported for conversational agents — iFrame embeds, Assistant, Microsoft Teams, Slack, and custom surfaces built with the UiPath TypeScript SDK. Monitor its performance, metrics, and user feedback through chat agent observability.
Available nodes
| Node | What it does |
|---|---|
| Conversation Trigger | Marks the Flow as conversational and starts it when a user initiates a chat on any channel. |
| Wait for Message | Suspends until the user sends a message, then outputs the latest conversation context (chat history) for downstream nodes to consume. |
| Conversational Agent | Runs a single chat agent turn. Streams its responses and takes actions through tool-calls. |
| Send Message | Writes an arbitrary message to the conversation. Use for fixed replies, routing messages, and emitting data from other nodes to the chat. |
| Get Conversation Context | Reads the current conversation history and metadata without suspending the Flow. Generally not needed, but can be used when a downstream node needs to inspect latest chat messages without waiting for new input. |
Capability examples
Combine the conversational nodes with the rest of Flow's palette to unlock a variety of capabilities, such as:
- Deterministic branching — route to different node paths based on message content or agent output.
- Agent hand-off — pass the conversation between multiple conversational agents, each with its own prompt and tools.
- Parallel branches — launch any other Flow branches in parallel - such as human approval tasks - while the conversation continues seamlessly to the user.
- Chat termination — end the conversation when a goal is reached.
- Zero-agent conversations — build a fully deterministic chat experience with no LLM turns at all.
End-to-end walkthrough
Visit build a chat agent workflow for a step-by-step example that combines the chat nodes into an agent-handoff routing pattern.
Related
- Chat conversational agents — surface overview in the Agents user guide.
- Chat deployment — publish to Orchestrator and expose through Instance Management, Assistant, Teams, Slack, iFrame, or the TypeScript SDK.