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.
Grok Bot logged into apps, cleaned and analyzed an inbox, drafted X and LinkedIn posts in the user's voice, and ran workflows overnight, pinging for decisions.
Grok Bot logged into apps, cleaned and analyzed an inbox, drafted X and LinkedIn posts in the user's voice, and ran workflows overnight, pinging for decisions.
The Grok bot was given access to the user's computer and apps. It logged into sites, clicked through them independently, cleaned and analyzed the inbox, then drafted X and LinkedIn posts in the user's voice. It watched one workflow, ran it overnight on its own, and pinged only when needing decisions or news updates; multiple bots coordinated with each other.
The bots managed and improved daily ops with ongoing coordination. On day 3 the user was still discovering additional capabilities.
Log into my email at [email provider] and clean my inbox: archive newsletters and promotions, and flag anything that needs a reply from me. Then read my recent posts on [X and/or LinkedIn] and draft [number] new posts in my voice about [topics]. Show me the drafts and a summary of the inbox changes, and do not publish or delete anything until I approve.
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.