customer_support · workflow
Assembled builds Cal, an LLM-powered agent-assist product for customer support
Customer support AI tools have focused on deflection to cut contact volume, but this still leaves handle time unaddressed so cost per case remains high. Assembled saw an opportunity to make agents faster rather than replace them.
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 · Agent needs answer or reply
Cal is designed to help agents quickly find answers and write replies.
Tools used
OpenAIZendesk · partner
Outcome
Re-engineering the auto-reply feature to be more interactive increased Cal's usage by 50%. Early users like Honeylove centered OKRs around increasing Cal's usage and improving its accuracy.
Results
Volume50%
Grounding & classification
Source type: technical build writeup
20 fields verified against source quotes.
agent assistcontent generationconversational airagknowledge basehuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedsoftwareemployee productivitytime savedtechnical build writeupcustomer supportai draft human approval