1.Catch Hook on live chat
Integrate Webhooks by Zapier and webhook parsing to receive the incoming chat webhook and map fields to source data.
Route incoming live chat to AI responder for triage
Automatically catch incoming live chat webhooks across Webhooks by Zapier and Formatter by Zapier. Send triaged conversation context to your AI endpoint when new chats arrive, so you can shorten agent response time, reduce context chasing, and handle every thread without manual copy-paste.
How this automation triages your live chats faster
When incoming chat webhooks arrive unstructured, agents can lose time hunting context and drafting first replies. This automation catches chat webhooks, normalizes message context, and posts it to your AI endpoint—so your team can respond with triaged context quickly.
Webhooks par Zapieror swap with your favorite app
2.Normalize chat context
Integrate Formatter by Zapier and text utilities to normalize timestamps, condense recent messages, and extract a thread identifier.
Formatter by Zapieror swap with your favorite app
3.Post context to AI
Integrate Webhooks by Zapier and API request headers to post the assembled JSON to your AI processing endpoint for triage.
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Speed up live chat response with automated chat routing, agent alerts, and conversation logging
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Étape 1
Connect your tools
Bring your apps together so information can move automatically between the tools your team already uses.
Étape 2
Define the trigger
Choose the events that should start your workflow, like a new submission, updated record, completed task, or customer action.
Étape 3
Automate and measure
Let your workflow handle follow-ups, updates, notifications, and reporting so your team can track progress and act faster.
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