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.
A personal agent runs at 7am, checks email, calendar and Todoist, pulls likely follow-ups and delivers one daily brief instead of the full inbox.
A personal agent runs at 7am, checks email, calendar and Todoist, pulls likely follow-ups and delivers one daily brief instead of the full inbox.
The poster built a personal agent that runs at 7am, reads their email, calendar, and Todoist, then sends one email with a daily summary, schedule, and likely follow-ups instead of making them scan everything themselves. In comments, they said each person gets their own assistant agent, and when they mark something as junk or correct a mislabeled email, that feedback is used to help train the agent for future runs.
They say it saves “way way too much time,” but give no hard metrics in the thread. It still mis-surfaces or mislabels items sometimes, and they fix those cases as part of improving it.
The clearest catch is that it needs ongoing correction: when it surfaces junk or labels something wrong, they manually fix it so the agent learns.
Every day at [7am, my time zone], check my email, my calendar, and my [Todoist or task app]. Send me one short brief with today's meetings, tasks due, and emails that likely need a follow-up from me, instead of the full inbox. Don't reply to, archive, or delete anything; just deliver the brief to [where I want it, e.g. email or chat].
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
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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.