Branch logicYour qualification logic. Not ours.
Branch instructions are configured per question. When a contact gives a negative answer, the AI applies the branch — ending the conversation, jumping to a different question, or offering to follow up. The logic is yours to define.
Structured tokens
Branch values can be structured tokens: END (end the conversation), REACH_BACK_OUT (offer to follow up), BOOKED (confirm a booking), or a question number (jump to Q3). The platform translates these into plain English instructions for the AI.
How it works: Token translation is tested — 'end the conversation', 'continue to Q3', 'offer to follow up later' are all rendered correctly in the system prompt.
Freeform instructions
Branch values can also be freeform prose — 'suggest the starter plan instead' or 'ask about their timeline before offering a demo'. The AI reads these as plain English instructions and applies them as part of its judgment.
How it works: Freeform branch instructions are passed through verbatim — they appear as Instruction lines in the decision tree summary visible to operators.
Auto-generated tree summary
A structured plain-text summary of the full decision tree is auto-generated alongside the question list. Every question, its positive path, and its branch outcome are described in plain English — readable by any operator without interpreting database fields.
How it works: Summary updates automatically when questions or branch values change — always reflects the current config the AI will receive.
Campaign Tester validation
Before any contact receives a qualified or rejected outcome, you can test every branch path in the Campaign Tester. Walk positive paths, trigger branch instructions manually, and confirm the AI applies them correctly.
How it works: Branch shortcuts in the Campaign Tester let you jump to specific question paths without manually simulating the full conversation from Q1.