Case Study
The System
AI appointment-setting architecture designed around messy real conversations, timing control, and CRM handoff constraints.
Debounced CRM workflow architecture
Proof Screenshots
Visual evidence for the operating path, workflow, or project contribution described in this case study.
Context
AI appointment-setting architecture designed around messy real conversations, timing control, and CRM handoff constraints.
The Problem
Prospects send fragmented messages, and simple bots respond too early or too rigidly.
Solution
GHL channel strategy, Supabase prompt/data layer, Trigger.dev timing control, n8n orchestration, and prompt UI.
Result
Defined a more inspectable AI workflow path where message timing, context, handoff, and human approval can be controlled.
Similar problem? Let's look at yours.
Start with the portfolio proof to inspect the CRM, automation, reporting, and business app patterns behind this work.
See Portfolio