Customer Support
A support lead who spends mornings triaging a queue that grew overnight while the product changed underneath the macros.
[ 01 ]The problem
Support tooling answers from canned macros, not from what the company actually knows. The refund policy changed two weeks ago, the macro didn't, and now an agent is confidently quoting the old terms. Every escalation costs a human pass, and the context — order history, prior threads, the policy doc — lives in four systems that the helpdesk can't see at answer time.
[ 02 ]How Mynd handles it
The queue becomes a plan
Y0 reads the inbound queue and plans the pass: which tickets are answerable from policy, which need account data, which must go to a human. Nothing is answered before it is classified.
Context loads before words do
For each ticket the context graph pulls the customer's order history, prior threads, and the current policy version — the current one, because the graph tracks document revisions, not snapshots.
Drafts with citations, escalations with reasons
The runtime drafts responses that cite the policy section they rely on, and escalates the rest with a one-line reason attached. The human queue shrinks to the tickets that genuinely need a human.
[ 03 ][ example run ]
plan ✦ triage 41 inbound tickets — overnight queue context ✓ refund policy v4 (current) — loaded context ✓ order history × 41 accounts — loaded context ✓ prior threads — 17 matched execute → draft 36 responses, policy cited inline execute → escalate 5 — reasons attached result ✓ 36 drafted · 5 escalated · 0 stale-policy citations
[ 04 ]of queue resolved without human touch
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