Voice for after-hours, chat for booking, dispatch automations, review reply, and the full integration map for ServiceTitan or Housecall Pro.
We have shipped the same core HVAC AI stack to 11 shops in the last 18 months. The stack is voice for after-hours, chat for booking, a dispatch automation layer, and a review-reply agent. Below: the full integration map for ServiceTitan or Housecall Pro, with the gotchas we hit in each. Why this is harder than it looks The most common failure mode with hvac for vertical businesses is treating the problem as a model selection problem. The hard parts are the data pipeline feeding it, the eval that catches regressions, and the human ownership layer that keeps the system honest after the implementer leaves the building.
The hard parts are the data pipeline feeding it, the eval that catches regressions, and the human ownership layer that keeps the system honest after the implementer leaves the building. We have shipped this category of system enough times to recognize a few patterns. The teams that win allocate roughly 20 percent of project time to the model and prompts, 40 percent to data and integrations, 25 percent to evals and observability, and 15 percent to change management. The teams that lose flip those numbers, spend 70 percent on prompts, and end up with a great demo that nobody trusts. The good news is that none of this is novel engineering.
Voice for after-hours, chat for booking, dispatch automations, review reply, and the full integration map for ServiceTitan or Housecall Pro. It is filed under Vertical Playbooks because that is where operators looking for this problem actually start, and it is written from production work rather than from a content calendar.