Answer patient enquiries for a clinic by chat
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
An OpenClaw agent drafted routine replies at about 70% ready quality and cut inbox processing from 10 to 2 minutes, though some things broke.
An OpenClaw agent drafted routine replies at about 70% ready quality and cut inbox processing from 10 to 2 minutes, though some things broke.
An agent named Donna, running on an OpenClaw gateway, got IMAP and Microsoft Graph access to three accounts. Every 30 minutes in business hours it sorted mail into urgent, important, informational and noise, pinged urgent items on Telegram, and drafted routine replies. It never sent anything without approval. It also read a memory file of relationship notes.
Triage was about 85% right, no urgent email was missed in 30 days, and routine drafts were about 70% ready. Tone, CC choices, context across sessions and relationship-sensitive emails went badly.
Define failure modes before deploying. The author narrowed the agent to routine, templated and newsletter mail, and had it flag negotiations, legal matters and established relationships without drafting.
Connect to my email accounts [list accounts] and go through unread messages from the last [time period]. Sort them into needs reply, FYI, and ignore, and write draft replies for the routine ones in my usual tone, which is [describe tone]. Save the drafts as drafts only and never send anything without asking me first. Finish with a short summary of what is waiting on me.
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
An n8n workflow has AI classify web-form jobs by type, urgency and summary, create an Airtable record, reply instantly and flag uncertain cases.
Lindy agents summarized meeting notes, sent action items to teammates, suggested knowledge-base replies on support tickets, and handled follow-up emails and calendar updates.