customer_support · saas · workflow
monday.com deploys Ada's AI Agent across chat and email channels, achieving 42% reduction in agent average handle time
monday.com's customer experience team handled high volumes of chat and email support globally, but their scripted chatbot approach was inflexible, hard to maintain, and required constant manual updates, leaving agents unable to focus on high-value tasks.
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 inquiry arrives
monday.com's customer experience team receives chats, emails, and callbacks globally across multiple channels.
Tools used
Ada
Outcome
With Ada's AI Agent deployed across chat and email, monday.com achieved a 42% reduction in agent average handle time and 64% CSAT on the chat channel, with containment rate growing month over month and substantial resource savings on email.
What failed first
Declarative, scripted chatbots were too rigid to dynamically handle customer inquiries and required constant manual intervention to stay current.
Results
Time saved42%
Volume64%
Grounding & classification
Source type: vendor customer story
33 fields verified against source quotes.
agentic workflowai agentconversational aisupport agentchat transcriptemailfailure mode describedhuman review describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedsoftwareautomation ratecost reductioncustomer satisfactiondeflection rateemployee productivityresolution time reductionvendor customer storycustomer supportautonomous resolutionescalation workflow