What Assembled learned by deploying its own voice AI in its support queue
Assembled's support operation relied heavily on tribal knowledge, and its knowledge base covered mainly the happy path — missing the edge-case documentation that AI requires to handle real customer queries consistently.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Customer calls support queue
A customer call enters Assembled's support queue and is received by the voice AI agent.
Tools used
AI voice agent
Outcome
Assembled had its first agentic workflows live within a few weeks, with support agents shifting toward editing and fact-checking AI outputs rather than handling routine queries directly, and workflow ownership becoming part of the support role itself.
What failed first
At a previous role, the support lead had over-focused on automating first-touch contacts without designing the broader workflow architecture, making the wider flow of work harder to manage. Early voice AI workflows at Assembled were also too rigid — structured like decision trees — causing the agent to keep asking for clarification even when the customer had already provided the needed context.