customer_support · saas · workflow
YAZIO deflects 80% of support tickets without lowering CSAT in 6 months with Forethought Solve
YAZIO's team of 5-8 agents could not keep up with rapidly increasing ticket volume while also managing help center content, templates, and internal knowledge bases; tickets went unanswered for too long and the team could not hire fast enough.
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 submits support request
Customers submit support requests through Solve's chatbot interface.
Tools used
ForethoughtSolveDiscover
Outcome
Solve deflected 80% of YAZIO's tickets in six months while maintaining a 4.0/5.0 CSAT, despite a 40% growth in ticket volume; the in-house team still manages the same workload as before without adding headcount.
What failed first
YAZIO had minimal success with an internal AI search tool, and other vendors they evaluated offered only rule-based chatbots built on large decision trees requiring regular maintenance—not true agentic AI.
Results
Time saved80%
Volume4.0/5.0
Grounding & classification
Source type: vendor customer story
37 fields verified against source quotes.
agentic workflowai agentchatbotconversational aisupport agentchat transcriptsupport tickethuman review describedmetric backednamed customerproduction runtime claimedsource backedtools describedworkflow describedhealthcaresoftwareautomation ratecustomer satisfactiondeflection rateemployee productivityvendor customer storycustomer supportticket triageautonomous resolutionescalation workflow